JP7023920B2 - Information processing equipment, information processing methods, and information processing programs - Google Patents

Description

The present invention relates to an information processing apparatus, an information processing method, and an information processing program.

Conventionally, techniques for forecasting various demands have been provided. For example, there is provided a technique for determining a user's needs information based on a user's search data including at least POI (Point of Interest) data.

Japanese Unexamined Patent Publication No. 2017-16625

However, it is not always possible to appropriately predict demand with the above-mentioned prior art. For example, since the above-mentioned conventional technique requires at least POI data, it may be difficult to appropriately predict demand when the POI data is insufficient or the POI data is inaccurate.

The present application has been made in view of the above, and an object thereof is to provide an information processing device, an information processing method, and an information processing program that appropriately estimate a consumption prospect or area of a demand target from various input information. And.

The information processing apparatus according to the present invention has a reception unit that receives input information including information related to the demand target input by the user, and an estimation unit that estimates a consumption prospective point or area of the demand target from the input information. The estimation unit is characterized in that a scene in which a demand target is required is estimated from the input information based on information including a pattern of input information and a scene in which a demand target corresponding to the pattern is required .

According to one embodiment of the present invention, it is possible to appropriately estimate the expected consumption point or area of the demand target from various input information.

FIG. 1 is a diagram showing an example of an information processing system. FIG. 2 is a diagram showing an example of a database that stores information including a pattern of input information and a scene in which a corresponding demand target is required. FIG. 3 is a diagram showing an example of a database that stores information about individual users. FIG. 4 is a diagram showing an example of a database that stores information including a pattern of input information and a scene in which a corresponding demand target is required. FIG. 5 is a diagram showing an example of a storage form of information including a combination of a demand target and a corresponding expected consumption area. FIG. 6 is a diagram showing an example of aggregated information. FIG. 7 is a diagram showing a configuration example of the information processing device. FIG. 8 is a diagram showing a configuration example of the terminal device. FIG. 9 is a flowchart summarizing an example of the flow of information processing. FIG. 10 is a diagram showing an example of a hardware configuration.

Hereinafter, various embodiments of the information processing apparatus, the information processing method, and the information processing program according to the present application will be described in detail with reference to the drawings. It should be noted that these embodiments do not limit the information processing apparatus, information processing method, and information processing program according to the present application. Further, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicate explanations are omitted.

[Embodiment]
[1. Information processing system 1]
An example of the information processing system 1 according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an example of an information processing system 1 according to an embodiment. As shown in FIG. 1, the information processing system 1 includes an information processing device 10, a business operator device 20, and a terminal device 100. The information processing system 1 may include a plurality of terminal devices 10, a plurality of business operator devices 20, and / or a plurality of information processing devices 100. Here, the information processing device 10, the operator device 20, and the terminal device 100 are communicably connected via a network N (see, for example, FIG. 7) via a network N (see, for example, FIG. 7).

The terminal device 100 is an information processing device used by the user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. In the example shown in FIG. 1, a case where the terminal device 100 is a smartphone is shown.

The terminal device 100 may collect information detected by various sensors (hereinafter, also referred to as “sensor information”). In this case, the terminal device 100 has various sensors and can detect various sensor information. The terminal device 100 has a function of an image sensor, and may detect and acquire image information (sensor information) of a user. The terminal device 100 has a function of a voice sensor such as a microphone, and may detect and acquire user voice information (sensor information). The terminal device 100 has various functions such as a heart rate sensor, and even if it can detect and acquire biological information (sensor information) such as a user's blood glucose level (blood glucose level information) and heart rate (heart rate information). good. The terminal device 100 may collect sensor information detected by a sensor other than its own device and transmit it to the information processing device 10.

The terminal device 100 has a function such as a GPS (Global Positioning System) sensor, and may detect and acquire the user's position information. The terminal device 10 may estimate and acquire the user's position information using the position information of the base station communicating with each other and the radio wave of WiFi (registered trademark) (Wireless Fidelity).

The terminal device 100 may have various functions such as a temperature sensor and a barometric pressure sensor, and may be able to detect and acquire environmental information such as temperature and barometric pressure in which the user is placed. The terminal device 10 has an acceleration sensor function, and may detect and acquire acceleration information in the movement of the user. For example, a user who uses the terminal device 100 may be able to acquire the user's own context information by the terminal device 100 by wearing a wearable device capable of communicating with the terminal device 100. For example, a user who uses the terminal device 100 wears a wristband-type wearable device capable of communicating with the terminal device 10, and the terminal device 10 acquires information on the user's own heartbeat (pulse) by the terminal device 10. It may be possible.

The terminal device 100 accepts operations by the user. Further, the terminal device 100 can transmit various information to the information processing device 10. For example, the terminal device 100 can send various input information such as tweets, e-mails, and search queries to the information processing device 10. Further, the terminal device 100 may be capable of transmitting information regarding various input situations such as position information.

The information processing apparatus 10 estimates the expected consumption point or area of the demand target from the input information including the information related to the demand target input by the user via the terminal device 100. The information processing apparatus 10 aggregates information including a combination of a demand target and a corresponding expected consumption point or area, creates aggregated information, and collects aggregated information in response to a request from the operator apparatus 20. Can be provided to.

The business operator device 20 is an information processing device used by a business operator. The business operator requests the information processing device 10 for aggregated information by using the business operator device 20 as necessary. The operator device 20 is realized by, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like.

Businesses that can obtain aggregated information via the business device 20 include, for example, clothes, shoes, personal belongings, various groceries, automobiles, bicycles, furniture, home appliances including convenience stores, supermarkets, home centers, mobile sales, etc. , Daily necessities, books, sporting goods, second-hand goods retailers; fast food restaurants including sushi, bento, ramen, dumplings, curry, bowls, hamburgers, ice cream, etc., Japanese restaurants, Western restaurants, Chinese restaurants , Grilled meat shops, restaurants, taverns, coffee shops, and other restaurants; cleaning services, accommodation services, car rental services, car sharing services, waste collection services, home delivery services, consulting services, and other service providers.

[1-1. Information processing flow in information processing system 1]
In the following description, the flow of information processing of the information processing system 1 will be described with reference to FIG.

First, the user inputs arbitrary input information from the terminal device 100 (step S1). The terminal device 100 transmits the input information to the information processing device 10 (step S2).

The information processing apparatus 10 receives the input information and estimates the expected consumption point or area of the demand target from the input information including the information related to the demand target (step S3). After that, the information processing apparatus 10 aggregates information including a combination of a demand target and a corresponding expected consumption point or area (step S4), creates aggregated information, and stores the aggregated information. The information processing apparatus 10 then provides aggregated information to the operator apparatus 20 in response to a request from the operator apparatus 20 (step S5) (step S6).

[1-2. Specific examples of information processing in information processing system 1]
Hereinafter, specific examples of information processing in one embodiment will be described with reference to FIGS. 2 to 6. In the present embodiment, it is assumed that the input information is a character string input to the search service.

Hereinafter, when user A (user ID: 001) inputs the character string "Akasaka curry" as input information (hereinafter referred to as "case 1"), user B (user ID: 002) inputs the character string "move". (Hereinafter referred to as "Case 2"), when user C (user ID: 003) inputs the character string "house cleaning" as input information (hereinafter referred to as "case 3"), user D (user ID:: When 004) inputs the character string "waste collection" as input information (hereinafter referred to as "case 4"), and when user E (user ID: 005) inputs the character string "home delivery" as input information (hereinafter referred to as "case 4"). 5 ”), when user F (user ID: 006) inputs the character string“ vending machine ”as input information (hereinafter referred to as“ case 6 ”), user G (user ID: 007) inputs the character string“ When "convenience store" is input (hereinafter referred to as "case 7"), when user H (user ID: 008) inputs the character string "thirsty" as input information (hereinafter referred to as "case 8"), user I (hereinafter referred to as "case 8") When the user ID: 009) inputs the character string "Cafe Power" as input information (hereinafter referred to as "Case 9"), and when the user J (user ID: 010) inputs the character string "Ekimae Hanaya" as input information. (Hereinafter referred to as "Case 10"), consumption forecast of the demand target based on 11 cases when the user K (user ID: 011) inputs the character string "car share" as input information (hereinafter referred to as "Case 11"). A specific example of area estimation will be described.

In Cases 1 to 11, it is assumed that the input information is input at Tokyo Tower (a specific point in Shibakoen 4-chome, Minato-ku) at 15:00:00 on a certain holiday, respectively. The terminal device 100 transmits the input information consisting of the character string input to the search service to the information processing device 10.

In Cases 1 to 11, information on the user ID (user ID: 001 to 011) of the input user, the time at the time of input (15:00:00), and the position at the time of input (Tokyo Tower) at the same time as the input information. Also, it is assumed that the information is transmitted to the information processing apparatus 10.

Further, in Cases 1 to 11, each user searches for a separate route from Tokyo Tower to Shinagawa Station (a specific point in Takanawa 3-chome, Minato-ku) immediately before inputting the input information (14:58:00). It is assumed that the route search information is recorded in the information processing apparatus 10 as user behavior information, and there is no subsequent route search record.

Case 1 is a case where the user A (user ID: 001) inputs the character string "Akasaka curry" as the input information. This character string contains information "curry" related to the demand target. The information processing apparatus 10 identifies the demand target "curry" from the information "curry" related to the demand target.

Such a demand target may be specified by using a database accumulating information including a pattern of input information and the corresponding demand target, or may use other known methods. In addition to the information related to the demand target, this character string contains information "Akasaka (place name of Minato Ward)" that can specify the expected consumption point or area.

In this case, it can be estimated that the information processing apparatus 10 is expected to consume the demand target "curry" in the "Akasaka" area.

In addition, if you wish to estimate the expected consumption area for each area by city, ward, town, or village, you can set the "Akasaka" based on the geographical information that the place name "Akasaka" belongs to "Minato Ward". It may be estimated that consumption of the demand target "curry" is expected in the "ward" area. Such geographic information may be recorded in the information processing apparatus 10 in advance.

Case 2 is a case where the user B (user ID: 002) inputs the character string "moving" as the input information. This string contains information "moving" related to the demand target. The information processing apparatus 10 identifies the demand target "moving service" from the information "moving" related to the demand target. Further, this character string does not include information that can specify a consumption prospective point or area such as "Akasaka" in Case 1.

In this case, the information processing apparatus 10 first uses a database that stores information including a pattern of input information and a scene in which a demand target corresponding to the pattern is required, and the demand target "moving service" in the input information "moving" is performed. Estimate the required scene.

FIG. 2 is a diagram showing an example of a database in which information including a pattern of input information and a corresponding scene in which a demand target is required, stored in the information processing apparatus 10 according to the embodiment is stored. In FIG. 2, four scenes relating to the position where the corresponding demand target is required are listed for each of various input information patterns, and which scene is suitable is summarized. It is assumed that the database shown in FIG. 2 is optimized by updating at an appropriate time based on the consumption trend of the demand target, and shows a scene that matches the actual consumption trend.

In FIG. 2, for convenience, the scenes related to the position where the demand target is required are set to "current location (other than home and work / school, the same applies hereinafter) area", "destination area", "home area", and "work / school area". Although limited to four scenes, the type of scene is not limited to these in the present invention.

In FIG. 2, the percentage shown in parentheses and one “○” and three “×” symbols are shown for each scene, but the percentage is expected to be consumed in each scene. The "○" symbol indicates the probability, the "○" symbol indicates the most suitable scene (that is, the scene with the highest probability of consumption), and the "x" indicates other scenes.

In Case 2, the input information is "moving", so referring to the line of the input information pattern "moving" in the database in Fig. 2, the most suitable scene where the demand target "moving service" is required is "home". It turns out that it is an area. Therefore, the information processing apparatus 10 estimates from the database of FIG. 2 that the scene where the demand target "moving service" is required from the input information "moving" is the "home area".

Next, after estimating the scene, the information processing apparatus 10 estimates that the point or area corresponding to the estimated scene is the expected consumption point or area. Since the estimated scene is the "home area", the information processing apparatus 10 first determines the home address from the attribute information of the user.

FIG. 3 is a diagram showing an example of a database that stores information about individual users stored in the information processing apparatus 10 according to the embodiment. FIG. 3 summarizes information about users for each user. The information about each user summarized in FIG. 3 includes user attribute information and user behavior information.

In the second case, the information processing apparatus 10 can identify that the input information is input by the user with the user ID "002" from the information of the user ID transmitted at the same time as the input information. By referring to the line of the user ID "002" in the database of FIG. 3, it can be seen that the address of the input user B is "Toyo ○ chome XX-XXX-102, Koto-ku, Tokyo".

Therefore, in Case 2, since the scene estimated as described above is the "home area", the information processing apparatus 10 has the "Koto-ku" area, the "Toyo" area, or the "Toyo ○ chome" corresponding to the estimated scene. It can be estimated that the area is the expected consumption area of the demand target "moving service".

By setting in advance the information processing device 10 a request for estimating the consumption expected area of the demand target for each area, the information processing device 10 can be set to the "Koto-ku" area and "Toyo". You can select either the "" area or the "Toyo ○ chome" area and estimate the expected consumption area that suits your purpose.

In the third case, the user C (user ID: 003) inputs the character string "house cleaning" as the input information. This string contains information "house cleaning" related to the demand target. The information processing apparatus 10 identifies the demand target "house cleaning service" from the information "house cleaning" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 3, as in Case 2, the information processing apparatus 10 estimates and estimates a scene in which the demand target “house cleaning service” in the input information “house cleaning” is required, using the database of FIG. It is estimated that the point or area corresponding to the scene is the expected consumption point or area.

In Case 3, the input information is "house cleaning", so referring to the row of the input information pattern "house cleaning" in the database in FIG. 2, the most suitable scene where the demand target "house cleaning service" is required. It turns out that is the "home area". Further, in Case 3, the input information can be identified from the user ID information as being input by the user with the user ID "003". Therefore, referring to the line of the user ID "003" in the database of FIG. 3, the input information is input. It can be seen that the address of the user C is "Toyo ○ chome XX-XXX-103, Koto-ku, Tokyo".

Therefore, in Case 3, since the scene estimated as described above is the "home area" in Case 3, the "Koto Ward" area, the "Toyo" area, or the "Toyo" area corresponding to the estimated scene is the same as in Case 2. It can be estimated that the Toyo ○ chome area is the expected consumption area of the demand target “house cleaning service”.

In the fourth case, the user D (user ID: 004) inputs the character string "waste collection" as the input information. This character string contains the information "waste collection" related to the demand target. The information processing apparatus 10 identifies the demand target "waste product collection service" from the information "waste product collection" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 4, as in Case 2, the information processing apparatus 10 estimates and estimates the situation in which the demand target “waste collection service” in the input information “waste collection” is required, using the database of FIG. It is estimated that the point or area corresponding to the scene is the expected consumption point or area.

In Case 4, since the input information is "Kerbside collection", it can be seen that the most suitable scene is the "home area" by referring to the line of the pattern "Kerbside collection" of the input information in the database of FIG. Further, in Case 4, the input information can be identified from the user ID information as being input by the user with the user ID "004". Therefore, referring to the line of the user ID "004" in the database of FIG. 3, the input information is input. It can be seen that the address of the user D is "Toyo ○ chome XX-XXX-104, Koto-ku, Tokyo".

Therefore, in Case 4, since the scene estimated as described above is the “home area” in Case 4, the “Koto Ward” area, the “Toyo” area, or the “Toyo” area corresponding to the estimated scene is the same as in Case 2. It can be estimated that the "Toyo ○ chome" area is the expected consumption area of the demand target "waste collection service".

Case 5 is a case where the user E (user ID: 005) inputs the character string "home delivery" as the input information. This character string contains information "home delivery" related to the demand target. The information processing apparatus 10 identifies the demand target "home delivery service" from the information "home delivery" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 5, as in Case 2, the information processing apparatus 10 estimates a scene in which the demand target “home delivery service” in the input information “home delivery” is required, and sets the estimated scene. Estimate the corresponding point or area as the expected consumption point or area.

In Case 5, the input information is "home delivery", so referring to the line of the input information pattern "home delivery" in the database in FIG. 2, the most suitable scene where the demand target "home delivery service" is required is "home". It turns out that it is an area. Further, in Case 5, the input information can be identified from the user ID information as being input by the user with the user ID "005". Therefore, referring to the line of the user ID "005" in the database of FIG. 3, the input information is input. It can be seen that the address of the user E is "Toyo ○ chome XX-XXX-105, Koto-ku, Tokyo".

Therefore, in Case 5, since the scene estimated as described above is the “home area” in Case 5, the “Koto Ward” area, the “Toyo” area, or the “Toyo” area corresponding to the estimated scene is the same as in Case 2. It can be estimated that the "Toyo ○ chome" area is the expected consumption area of the demand target "home delivery service".

In the sixth case, the user F (user ID: 006) inputs the character string "vending machine" as the input information. This character string contains information "vending machine" related to the demand target. The information processing apparatus 10 identifies the demand target "beverage" from the information "vending machine" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 6, as in Case 2, the information processing apparatus 10 estimates a scene in which the demand target “beverage” in the input information “vending machine” is required, and uses the database of FIG. 2 to estimate the scene. Estimate the corresponding point or area as the expected consumption point or area.

In Case 6, the input information is "vending machine", so referring to the line of the input information pattern "vending machine" in the database in Fig. 2, the most suitable scene where the demand target "beverage" is needed is "current location". It turns out that it is an area. From the information on the position at the time of input sent at the same time as the input information, it can be seen that the input information was input at "Tokyo Tower".

Therefore, in Case 6, since the scene estimated as described above is the "current location area" in the information processing apparatus 10, consumption of the demand target "beverage" is expected in the "Tokyo Tower" area corresponding to the estimated scene. Can be estimated. Also, as in Case 1, based on the geographical information that "Tokyo Tower" belongs to "Minato-ku Shibakoen 4-chome", the "Minato-ku" area, "Shibakoen" area, or "Shiba" It may be estimated that the demand target "beverages" are expected to be consumed in the "Park 4-chome" area.

Case 7 is a case where the user G (user ID: 007) inputs the character string "convenience store" as the input information. This character string contains information "convenience store" related to the demand target. The information processing apparatus 10 identifies the demand target "service at the convenience store" from the information "convenience store" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 7, as in Case 2, the information processing apparatus 10 estimates and estimates the scene where the demand target “service at the convenience store” in the input information “convenience store” is required by using the database of FIG. It is estimated that the point or area corresponding to is the expected consumption point or area.

In Case 7, the input information is "convenience store", so referring to the row of the input information pattern "convenience store" in the database in FIG. 2, the most suitable scene where the demand target "service at convenience store" is required is " It turns out that it is the "current location area". In addition, it can be seen that the input information was input by "Tokyo Tower" from the information of the position at the time of input transmitted at the same time as the input information.

Therefore, in Case 7, the information processing apparatus 10 covers the "Tokyo Tower" area, "Minato Ward" area, "Shiba Park" area, or "Shiba Park 4-chome" area as the demand target "at the convenience store" as in Case 6. It can be estimated that it is the area where the service is expected to be consumed.

Case 8 is a case where the user H (user ID: 008) inputs the character string "thirsty" as the input information. This string contains information "thirsty" related to the demand target. The information processing apparatus 10 identifies the demand target "beverage" from the information "thirsty" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 8, as in Case 2, the information processing apparatus 10 estimates and estimates the scene in which the demand target “beverage” in the input information “thirsty” is required, using the database of FIG. It is estimated that the point or area corresponding to the scene is the expected consumption point or area.

In Case 8, the input information is "thirsty", so referring to the line of the input information pattern "thirsty" in the database of FIG. 2, the demand target "beverage" is most suitable. You can see that the scene is the "current location area". In addition, it can be seen that the input information was input by "Tokyo Tower" from the information of the position at the time of input transmitted at the same time as the input information.

Therefore, in Case 8, the information processing apparatus 10 supplies the "Tokyo Tower" area, "Minato Ward" area, "Shibakoen" area, or "Shibakoen 4-chome" area as the demand target "beverages" as in Case 6. It can be estimated that it is an area where consumption is expected.

Case 9 is a case where the user I (user ID: 009) inputs the character string "cafe power supply" as the input information. This string contains information "cafe power" related to the demand target. The information processing apparatus 10 identifies the demand target "service in the cafe including charging" from the information "cafe power supply" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 9, as in Case 2, the information processing apparatus 10 uses the database of FIG. 2 to estimate the situation where the demand target “service in the cafe including charging” in the input information “cafe power supply” is required. , It is estimated that the point or area corresponding to the estimated scene is the expected consumption point or area.

In Case 9, the input information is "cafe power supply", so referring to the line of the input information pattern "cafe power supply" in the database in FIG. 2, the demand target "service in the cafe including charging" is the most necessary. It can be seen that the suitable scene is the "destination area". Further, the information processing apparatus 10 can identify that the input information is input by the user I of the user ID "009" from the information of the user ID transmitted at the same time as the input information. Referring to the line of the user ID "009" in the database of FIG. 3, the information that the user I is searching for the route from Tokyo Tower to Shinagawa Station immediately before inputting the input information is recorded as the user's action information. Has been done.

Therefore, in Case 9, the information processing apparatus 10 identifies the area corresponding to the estimated scene as the "Shinagawa Station" area, and the demand target "service in the cafe including charging" is consumed in the "Shinagawa Station" area. It can be estimated that it is expected. Also, as in Case 1, based on the geographical information that "Shinagawa Station" belongs to "Takanawa 3-chome, Minato-ku", depending on the setting based on wishes, the "Minato-ku" area, "Takanawa" area, or "Takanawa 3-chome" It may be estimated that the demand target "services in cafes including charging" is expected to be consumed in the area.

In the case 10, the user J (user ID: 010) inputs the character string "Ekimae Hanaya" as the input information. This string contains information "florist" related to the demand target. The information processing apparatus 10 identifies the demand target "flowers" from the information "florist" related to the demand target. In addition, since it is not possible to specify which station front is "in front of the station" in this character string, it cannot be said that this character string contains information that can specify the expected consumption point or area.

Therefore, in Case 10, as in Case 2, the information processing apparatus 10 estimates and estimates the scene where the demand target "flowers" in the input information "flower shop in front of the station" is required by using the database of FIG. It is estimated that the point or area corresponding to is the expected consumption point or area.

In Case 10, the input information is "Ekimae Hanaya", so referring to the line of the input information pattern "Ekimae Hanaya" in the database in Fig. 2, the most suitable scene where the demand target "flowers" is required is It can be seen that it is a "destination area". Further, the information processing apparatus 10 can identify that the input information is input by the user J of the user ID "010" from the information of the user ID transmitted at the same time as the input information. Referring to the line of the user ID "010" in the database of FIG. 3, the information that the user J is searching for the route from Tokyo Tower to Shinagawa Station immediately before inputting the input information is recorded as the user's action information. Has been done.

Therefore, in Case 10, the information processing apparatus 10 identifies the area corresponding to the estimated scene as the "Shinagawa Station" area, and as in Case 9, the "Shinagawa Station" area, the "Minato Ward" area, and the "Takanawa". It can be estimated that consumption of the demand target "flowers" is expected in the area or the "Takanawa 3-chome" area.

In the eleventh case, the user K (user ID: 011) inputs the character string "car share" as the input information. This character string contains information "car share" related to the demand target. The information processing apparatus 10 identifies the demand target "car sharing service" from the information "car sharing" related to the demand target. In addition, this character string does not contain information that can identify the expected consumption point or area.

Therefore, in Case 11, as in Case 2, the information processing apparatus 10 estimates and estimates a scene in which the demand target “car sharing service” in the input information “car sharing” is required, using the database of FIG. It is estimated that the point or area corresponding to the scene is the expected consumption point or area.

In Case 11, the input information is "car sharing", so referring to the row of the input information pattern "car sharing" in the database in FIG. 2, the most suitable scene where the demand target "car sharing service" is required. It turns out that is the "current location area". In addition, it can be seen that the input information was input by "Tokyo Tower" from the information of the position at the time of input transmitted at the same time as the input information.

Therefore, in Case 11, the information processing apparatus 10 supplies the "Tokyo Tower" area, "Minato Ward" area, "Shibakoen" area, or "Shibakoen 4-chome" area as the demand target "beverages" as in Case 6. It can be estimated that it is an area where consumption is expected.

The database of FIG. 2 contains only one type of information for one input information pattern, but the most suitable scene in which the demand target "car sharing service" is required in the input information pattern "car sharing". Although it is the "current location area (33%)", there is a high probability that consumption is expected in the "destination area (27%)" and "home area (25%)".

In this way, depending on the pattern of input information, scenes with a relatively high probability of consumption may be dispersed. In order to correspond to such an input information pattern, even if the scene where the demand target is required for one input information pattern is stored for each pattern in which the consumption tendency of the demand target is different. good.

FIG. 4 is a diagram showing an example of a database in which information including a pattern of input information and a corresponding scene in which a demand target is required, stored in the information processing apparatus 10 according to the embodiment is stored. The database of FIG. 4 stores the scenes relating to the position where the demand target is required for each pattern in which the consumption tendency of the demand target is different for the input information pattern “car share”. In the database of FIG. 4, the time at the time of input, the age of the input person, and the gender of the input person are used as patterns in which the consumption tendency of the demand target is different.

Hereinafter, with respect to Case 11, a specific example of estimation of the expected consumption area by the information processing apparatus 10 when the database of FIG. 4 is used instead of the database of FIG. 2 will be described.

In the eleventh case, it can be identified that the input information is input by the user K of the user ID "011" from the information of the user ID transmitted at the same time as the input information. By referring to the line of the user ID "011" in the database of FIG. 3, it can be seen that the gender of the input user K is "male" and the age of the user K is "32 years old". Further, from the input time information transmitted at the same time as the input information, it can be seen that the input information was input at 15:00:00 on a holiday.

Based on the above information, in the database of FIG. 4, the input information pattern "car share", input time "holiday" and "12:00 to 16:00", user's gender "male" and user's age "30 to 39 years old" If you refer to the line corresponding to, you can see that the most suitable scene where the demand target "car sharing service" is required is the "destination area".

Referring to the line of the user ID "011" in the database of FIG. 3, the information that the user K is searching for the route from Tokyo Tower to Shinagawa Station immediately before inputting the input information is recorded as the user's action information. Has been done. Therefore, the information processing apparatus 10 identifies the area corresponding to the estimated scene as the "Shinagawa Station" area, and as in Case 9, the "Shinagawa Station" area, the "Minato Ward" area, the "Takanawa" area, or the "Takanawa" area. It can be estimated that the demand target "car sharing service" is expected to be consumed in the "Takanawa 3-chome" area.

After estimating the expected consumption point or area of the demand target from the input information, the information processing apparatus 10 stores the information including the combination of the demand target and the corresponding expected consumption point or area. FIG. 5 is a diagram showing an example of a storage form of information including a combination of a demand target and a corresponding consumption prospect area stored in the information processing apparatus 10 according to the embodiment. FIG. 5 shows information data including 50 demand targets and expected consumption areas estimated by the information processing apparatus 10 at 15:00:00 in the present embodiment.

After that, the information processing apparatus 10 aggregates information including a combination of a demand target and a corresponding expected consumption point or area, creates aggregated information, and stores the aggregated information. FIG. 6 is a diagram showing an example of aggregated information stored in the information processing apparatus 10 according to the embodiment. FIG. 6 is aggregated information for each area of the expected consumption area for the demand target “beverage” estimated by the information processing apparatus 10 in 1 second at 15:00:00 in the present embodiment.

[2. Configuration of information processing device 10]
Next, an example of the functional configuration of the information processing apparatus 10 according to the embodiment will be described with reference to FIG. 7. FIG. 7 is a diagram showing a configuration example of the information processing apparatus 10 according to the embodiment. As shown in FIG. 7, the information processing apparatus 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. Then, the communication unit 11 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the terminal device 100 and the operator device 20.

The storage unit 12 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. Further, the storage unit 12 includes a reception information storage unit 121, an area information storage unit 122, a scene information storage unit 123, an individual information storage unit 124, an estimation information storage unit 125, and an aggregate information storage unit 126.

The reception information storage unit 121 stores the input information that each user inputs via the terminal device 100 and is transmitted from the terminal device 100 to the information processing device 10. Further, the reception information storage unit 121 may store, together with the input information, information for identifying the input person and information regarding the situation at the time of input (hereinafter, both information are collectively referred to as "accompanying information"). The information for identifying the input person is information for specifying which user the person (input person) who input the input information is, for example, the user ID of the input user and the terminal ID of the input user. , IP address, etc. The information regarding the situation at the time of input may be information such as the time at the time of input, the position or area at the time of input, the weather at the time of input, the input method, the heart rate at the time of input, the balance of electronic money at the time of input, and the like.

The accompanying information stored in the reception information storage unit 121 is automatically created by the terminal device 100 based on the physical sensor 140 such as GPS possessed by the terminal device 100, and is simultaneously or continuously from the terminal device 100 with the input information. It may be information transmitted to the information processing apparatus 10. Further, the accompanying information stored in the reception information storage unit 121 is automatically created by the terminal device 100, and is information based on the information transmitted from the terminal device 100 to the information processing device 10 simultaneously or continuously with the input information. In the processing device 10, for example, the information may be created in the reception unit 131. In this case, in the present specification, the information transmitted to the information processing apparatus 10 and the information created by the information processing apparatus 10 are both referred to as incidental information.

The input information stored in the reception information storage unit 121 may include information related to the demand target. The information related to the demand target may be any information that can objectively identify a certain demand target. One input information may include information related to one type of demand target, or may include information related to two or more types of demand targets.

The input information stored in the reception information storage unit 121 may include information input by the user consciously or unknowingly in search of a demand target. Therefore, the demand target may be what the user feels necessary at the time of input, but is not limited to what is immediately available.

The input information stored in the reception information storage unit 121 is information directly related to the demand target (hereinafter referred to as "direct information"), information indirectly related to the demand target (hereinafter referred to as "indirect information"), or. It may include combinations thereof.

Direct information includes, for example, character strings directly related to the demand target, images directly related to the demand target, videos directly related to the demand target, sounds directly related to the demand target, and the like. Combinations and the like can be mentioned. The direct information specifically includes the meaning of apples such as "apple", "apple", "apple", "apple", "royal apple (a kind of apple)" if the demand target is apple. It can be a character string, an image representing an apple, a video showing an apple, a sound of biting an apple, or the like.

As indirect information, for example, in a blog, an electronic store, an advertisement, a video image sharing service, etc., the user selects a specific option in a reference request information, a questionnaire, etc. input by the user to refer to a video, an image, a sound, or the like. Examples include the selection information entered for this purpose. Specifically, if the demand target is an apple, the indirect information may be reference request information for an apple sales advertisement, selection information that an apple was selected in a questionnaire about the fruit to be eaten now, and the like.

In the input information stored in the reception information storage unit 121, the demand target is a product or service that can be consumed by the consumer, may be a specific product or service, or is an abstract product or service category. May be. The information related to the demand target may be not only the direct information of the goods or services but also the information that objectively associates the goods or services. For example, when the input information is a character string, the information related to the demand target is not only the nomenclature of the product or service itself such as "apple" and "tangerine", but also the "umbrella" when the input information is "rain". , If the input information is "driving", "car", if the input information is "moving", "moving service", if the input information is "thirsty", "beverage", the input information is " If "I have a stomachache", it may be a character string that can objectively associate a certain product or service, such as "stomach medicine".

The input information stored in the reception information storage unit 121 may include information that can specify an expected consumption point or area (hereinafter referred to as "point area identification information") in addition to information related to the demand target. be. When the input information stored in the reception information storage unit 121 includes the point area specific information, the expected consumption point or area is estimated based on the point or area. In one embodiment, the input information stored in the reception information storage unit 121 includes the point area identification information. In one embodiment, the input information stored in the reception information storage unit 121 does not include the point area specific information.

The point area specific information in the input information may be any information that can objectively identify a specific point or a specific area. Information that can objectively identify a specific point includes railway stations, bus stops, bridges, parks, condominiums, apartments, buildings, schools, public facilities / government offices, hospitals, shrines / temples, landmarks, commercial facilities, factories, and intersections. , Name, common name or abbreviation of a specific place such as a historic site; it may be information indicating a specific point such as a specific address including an address / number, latitude and longitude. Information that can objectively identify a specific area includes information indicating a certain geographical range such as prefectures, municipalities, towns / characters / chomes, district names, common names or abbreviations; railway lines, roads, streets. , Information that gives rise to a certain geographical range such as river names, common names or abbreviations.

The point area identification information in the input information must be able to directly specify the expected consumption point or area. If you want to estimate the expected consumption area for each area (when you set the area unit setting information), the point area specific information in the input information can specify a specific point, or the area unit setting information It may be information that can identify an area equivalent to or narrower than the area unit. For example, when you want to estimate the expected consumption area for each area by city, such as "A city" or "B town" (when the area unit of the area unit setting information is set to the city, ward, town, or village unit). ), Even if the input information contains information that can identify a point or area, if it is "C prefecture", "D region", or "E country", it indicates a wide area compared to the municipality unit. Therefore, it cannot be said that it is point area specific information.

The input method of the input information stored in the reception information storage unit 121 is not particularly limited as long as the user can input the input information via the terminal device 100. Input information is a search service, SNS (Social Networking Service) such as Twitter (registered trademark) and Facebook (registered trademark), message service such as LINE (registered trademark), e-mail, electronic bulletin board, chat, posting service, upload service. It may be input information input by the user via such as.

The geographic information storage unit 122 stores reference geographic information as a reference when estimating a consumption prospecting point or area of a demand target. The reference geographic information stored in the geographic information storage unit 122 may be the same as the information that can be included in a commercially available or publicly available map. Standard geographic information includes specific locations such as railway stations, bus stops, bridges, parks, apartments, apartments, buildings, schools, public facilities / government offices, hospitals, shrines / temples, landmarks, commercial facilities, factories, intersections, historic sites, etc. Name, common name or abbreviation, specific address including address / number, location information such as latitude / longitude; area information such as prefectures, cities, wards, towns and villages, towns / characters / chomes, districts, etc. It may be included. The reference geographic information may include information on any section set by any method. Any section set by any method may be, for example, a section of any size divided in a grid pattern.

For the reference geographic information stored in the geographic information storage unit 122, when it is desired to estimate the consumption expected area of the demand target for each area, further, in what area unit the consumption expected area of the demand target is estimated for each area. It may include area unit setting information for which a reference is set. Examples of the area unit in the area unit setting information include prefecture unit, city / ward / town / village unit, town / character / chome unit, district unit, street number unit, and the like. Further, the area unit in the area unit setting information may be an arbitrary section unit set by an arbitrary method.

The scene information storage unit 123 needs a pattern of input information (hereinafter referred to as “input pattern”) and a scene in which a corresponding demand target is required (hereinafter referred to as “demand required”) in order to estimate a scene in which a demand target is required from the input information. Stores a database (hereinafter referred to as "scene information database") that stores information including (sometimes referred to as "scene"). That is, the scene information storage unit 123 stores demand-required scenes for each input pattern. The scene information database stored in the scene information storage unit 123 is a database that stores, when a user inputs certain input information, in what situations the user needs a demand target for the input information for each input information. Can be.

In the scene information database stored in the scene information storage unit 123, the input information of the input pattern includes information related to the demand target. Further, the input information of the input pattern may not include the point area specific information. The input pattern may be various input patterns such as an input pattern that has been input so far, an input pattern that is expected to be input in the future, and / or an input pattern that may be input in the future. The demand-required scene can be a scene relating to the position where the demand target is needed. The demand-required scene is, for example, a scene where the current location or current location area when the input information is input, a movement point or a destination area which is estimated to move after the input information is input, or the like is not fixed; the user's home location or It may be a fixed scene such as a home area, a user's workplace / school location, or a workplace / school area.

The scene information database stored in the scene information storage unit 123 includes one or more demand-required scenes for one input pattern. When the scene information database of the scene information storage unit 123 includes two or more demand-requiring scenes for one input pattern, one input pattern and two or more demand-requiring scenes are consumed by each scene. It may be included with information for identifying the expected degree or frequency (hereinafter referred to as "frequency information"). The frequency information can be, for example, information based on variables such as score, probability (for example, percentage), cumulative number of cases, and the like. There may be at least one frequency information for one demand-required situation.

The scene information storage unit 123 serves as a scene information database, for example, for the input patterns A1, B1 and C1 to the current location (the demand-required scene is the current location area), and for the input pattern D1, the destination (the demand-required scene moves). One input such as home for input patterns E1 and F1 (home area where demand is required), workplace / school for input pattern G1 (work / school area where demand is required), and so on. You may memorize one demand scene that is most expected to be consumed for the pattern, or for the input pattern A2, "current location 11%, destination 5%, home 72%, work / school 12%". For example, two or more demand-requiring situations for one input pattern may be stored together with frequency information.

In addition to the input pattern, the scene information storage unit 123 may store demand-required scenes according to a pattern in which the consumption tendency of the demand target is different (hereinafter referred to as “variation pattern”). That is, the scene information database stored in the scene information storage unit 123 includes a combination of an input pattern and a pattern in which the consumption tendency of the demand target is different (hereinafter referred to as “variation pattern”) and a demand necessary scene corresponding to the combination. It may be a database that stores information. Fluctuation patterns include, for example, the age of the input person, the gender of the input person, the family structure of the input person, the income of the input person, the occupation of the input person, the attributes of the input person such as the hobby or interest of the input person, and the time at the time of input. , The place at the time of input, the area at the time of input, the weather at the time of input, the input method, the heart rate at the time of input, the situation at the time of input such as the balance of electronic money at the time of input, and the like. The variation pattern may be one or a combination of two or more for one input pattern.

As a scene information database, the scene information storage unit 123 is, for example, "current location" in the morning (at the time of input) and under the age of 20 (input person), and in the afternoon (at the time of input) and 20 for the input pattern A3. "Destination" for under age (input person), "home" for morning (at the time of input) and 20 years old or older (input person), afternoon (at the time of input) and 20 years old or older (input person) In the case, one demand-required scene may be stored for one combination of input pattern and fluctuation pattern, such as "work / school".

As a scene information database, the scene information storage unit 123 is, for example, for the input pattern A4 in the morning (at the time of input) and in the case of a woman (input person), "current location 11%, destination 5%, home 72%, Work / school 12% ”, afternoon (at the time of input) and for women (input person)“ current location 9%, destination 6%, home 71%, work / school 14% ”, morning (at the time of input) In the case of male (input person), "current location 22%, destination 2%, home 53%, work / school 23%", in the afternoon (at the time of input) and in the case of male (input person), "current location 18%, move" Two or more demand-required situations may be stored together with frequency information for one combination of input patterns and fluctuation patterns, such as "5% at home, 52% at home, 25% at work / school".

The scene information database stored in the scene information storage unit 123 may further store information including whether or not there is a demand target corresponding to the input pattern. Further, the scene information database stored in the scene information storage unit 123 may further store information including a demand target corresponding to a pattern of input information.

The individual information storage unit 124 stores information about individual users (hereinafter referred to as "individual information"). The individual information stored in the individual information storage unit 124 may be, for example, various information such as user attribute information and user behavior information. User attribute information includes the user's age, user's gender, user's family structure, user's name, user's income, user's occupation, user's hobbies or interests, user's home address, user's workplace or school. Addresses, etc. may be included, but are not limited to these. The user behavior information may include, but is not limited to, a user's movement history, a user's search history, a user's purchase history, a user's call history, and the like. In addition to the individual information, in order to identify the user corresponding to the input person, information for identifying the input person corresponding to each individual information such as a user ID and a terminal ID may be included. The user attribute information and the user behavior information may be information stored in the individual information storage unit 124 in advance before the reception unit 131 receives the input information.

The estimation information storage unit 125 stores information including a combination of the demand target and the expected consumption point or area of the demand target estimated by the estimation unit 132 (hereinafter referred to as “estimation result information”). The estimation information storage unit 125 accumulates estimation result information each time the estimation unit 132 performs estimation processing. The estimation information storage unit 125 may store a combination of a demand target and its expected consumption point or area together with other information. Other information may be information about the input pattern, information about the situation at the time of input including accompanying information, and / or information about the attributes of the user. The information regarding the situation at the time of input may be the corresponding incidental information or may be information other than the corresponding incidental information. The information regarding the situation at the time of input may be, for example, the same as the incidental information. Information on the attributes of the user includes, for example, the age of the user, the gender of the user, the family structure of the user, the income of the user, the occupation of the user, the hobby or interest of the user, and the like.

The aggregated information storage unit 126 stores the aggregated information created by aggregating two or more estimation result information in the aggregated information unit 133. The aggregated information stored in the aggregated information storage unit 126 includes a combination of a demand target and a corresponding expected consumption point or area, but is aggregated. The aggregated information stored in the aggregated information storage unit 126 is in any format such as the degree or frequency of the expected consumption of the demand target for each area and the distribution of the expected consumption of the demand target, and the format of the aggregated information is according to the purpose. You just have to decide. The aggregated information stored in the aggregated information storage unit 126 is classified by input pattern; user's age, user's gender, user's family structure, user's income, user's occupation, user's hobby or interest type. Input by user attributes such as; and / or by time at the time of input, by area at the time of input, by weather at the time of input, by heart rate at the time of input, by input method, by balance of electronic money at the time of input, etc. It may be aggregated according to the situation at the time.

The control unit 13 is realized by, for example, using a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like to execute various programs stored in a storage device inside the information processing device 10 using the RAM as a work area. Will be done. Further, the control unit 13 is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in FIG. 7, the control unit 13 includes a reception unit 131, an estimation unit 132, an aggregation unit 133, and a provision unit 134.

The reception unit 131 receives the input information input by the user via the terminal device 100 from the terminal device 100. In the present invention, the input information received by the reception unit 131 may include information related to the demand target input by the user. Therefore, the reception unit 131 receives input information including information related to the demand target input by the user.

The reception unit 131 selects input information including information related to the demand target from the received input information, stores only the input information including the information related to the demand target in the reception information storage unit 121, and the demand target is It is not necessary to store the input information that cannot be specified (that is, the input information that does not include the information related to the demand target) in the reception information storage unit 121. The reception unit 131 temporarily stores all the received input information in the reception information storage unit 121, and in the estimation unit 132 described below, the reception unit 132 stores information related to the demand target from the input information stored in the reception information storage unit 121. You may select the input information to be included.

The selection of input information including information related to the demand target is performed using a database (hereinafter referred to as "demand target existence determination database") that stores information including the input pattern and whether or not the corresponding demand target exists. You may. The demand target existence determination database may store information on whether or not information related to the demand target is included for each input pattern. The reception unit 131 or the estimation unit 132 is based on information on the presence or absence of a demand target corresponding to an input pattern that matches the input information stored in the reception information storage unit 121 among the input patterns stored in the demand target existence determination database. Determine if the input information contains information related to the demand target. The demand target existence determination database may be the same database as the scene information database. In addition, for the selection of the input information including the information related to the demand target, a known method for determining the presence or absence of the demand target from the input information may be used.

The reception unit 131 may accept the input information together with the accompanying information. The reception unit 131 may receive the input information and the accompanying information at the same time or continuously. The input information and accompanying information received by the reception unit 131 are stored in the reception information storage unit 121 as they are or after being converted into an appropriate format.

The estimation unit 132 estimates the expected consumption point or area of the demand target from the input information stored in the reception information storage unit 121. The estimation unit 132 identifies the demand target from the information related to the demand target included in the input information.

The demand target can be identified from the information related to the demand target included in the input information by using a database (hereinafter referred to as "demand target database") that stores information including the input information pattern and the corresponding demand target. good. The demand target database may store the information of the demand target corresponding to each input pattern. In this case, the estimation unit 132 sets the demand target corresponding to the input pattern matching the input information stored in the reception information storage unit 121 among the input patterns stored in the demand target database to the demand target corresponding to the input information. Identify as. The demand target database may be the same database as the scene information database. In addition, for specifying the demand target from the information related to the demand target included in the input information, a known method for identifying the demand target from the input information may be used.

Further, the demand target may be specified from the information related to the demand target included in the input information at the same time as the selection of the input information including the information related to the demand target. In this case, the demand target existence determination database and the demand target database may be the same database.

When the input information stored in the reception information storage unit 121 includes the point area specific information, the estimation unit 132 estimates the expected consumption point or area based on the point or area. The estimation unit 132 may estimate the estimated consumption point or area from the point area specific information included in the input information based on the reference geographic information stored in the geographic information storage unit 122. The estimation unit 132 calculates a point or area specified by the point area specific information included in the input information from the point information or area information of the reference geographic information stored in the geographic information storage unit 122, and the index is determined. The point or area corresponding to the geographical information may be estimated as the expected consumption point or area.

When the estimation unit 132 wishes to estimate the expected consumption area of the demand target for each area (when the area unit setting information is set), the estimation unit 132 geographically determines the point or area specified by the point area specific information included in the input information. It may be determined from the point information or area information of the reference geographic information stored in the information storage unit 122, and an appropriate area corresponding to the reference geographic information may be estimated as a consumption expected area based on the area unit setting information. The estimation unit 132 is, for example, when it is desired to estimate the consumption expected area of the demand target for each area in the city, ward, town, or village unit (when the area unit of the area unit setting information is set in the city, ward, town, or village unit), and the point area. If the specific information is the place name "A town 1-chome", the area specified by "A town 1-chome" is determined to be "C prefecture B city A town 1-chome" from the standard geographic information, and the area unit Based on the setting information, it can be estimated that "City B" is the expected consumption area.

When the input information stored in the reception information storage unit 121 does not include the point area specific information, the estimation unit 132 estimates a scene in which a demand target is required from the input information, and the estimation unit 132 estimates a scene in which a demand target is required, and a point or area corresponding to the estimated scene. Is estimated to be a prospective consumption point or area.

The estimation unit 132 may estimate a scene in which a demand target is required from the input information stored in the reception information storage unit 121 based on the scene information database stored in the scene information storage unit 123. In this case, the estimation unit 132 needs a demand target in the input information for a demand-required scene corresponding to the input pattern matching the input information stored in the reception information storage unit 121 among the input patterns in the scene information database. It is presumed that this is the scene.

The estimation unit 132 needs a demand target in the input information for one demand-required scene corresponding to the input pattern matching the input information stored in the reception information storage unit 121 among the input patterns in the scene information database. It may be presumed to be a scene (for example, the above-mentioned examples of input patterns A1 to G1).

The estimation unit 132 is the most expected consumption based on the frequency information from two or more demand-requiring scenes corresponding to the input patterns matching the input information stored in the reception information storage unit 121 among the input patterns in the scene information database. One scene with a high degree or frequency of (For example, the above example of the input pattern A2: In the case of the above example, the most frequent "home" is estimated).

Among the input patterns in the scene information database, the estimation unit 132 uses the input information as it is for demand targets for two or more demand-requiring scenes corresponding to the input patterns that match the input information stored in the reception information storage unit 121. (For example, in the above example of input pattern A2: "Current location 11%, Destination 5%, Home 72%, Work / school 12%"" Estimate four scenes with frequency information). In this case, each scene is processed by associating it with the frequency information, and the frequency information associated with each scene is used after the estimated consumption point or area is estimated from the estimated scene and then each corresponding consumption expected point. Or it is linked to the area.

In the scene information database stored in the scene information storage unit 123, the estimation unit 132 stores the demand required scenes in the reception information storage unit 121 among the input patterns in the scene information database when the demand required scenes are stored for each fluctuation pattern. One demand-requiring scene corresponding to an input pattern matching the input information and the most suitable fluctuation pattern may be estimated to be a scene in which the demand target is required in the input information (for example, in the above input pattern A3). example). In this case, the most suitable variation pattern may be selected based on the accompanying information stored in the reception information storage unit 121 and / or the individual information stored in the individual information storage unit 124 (in the example of the input pattern A3). If there is, it is selected based on the time at the time of input stored as incidental information in the reception information storage unit 121 and the age of the user stored in the individual information storage unit 124).

In the scene information database stored in the scene information storage unit 123, the estimation unit 132 stores the demand required scenes in the reception information storage unit 121 among the input patterns in the scene information database when the demand required scenes are stored for each fluctuation pattern. It may be estimated that two or more demand-requiring scenes corresponding to the input pattern matching the input information and the most suitable fluctuation pattern are the scenes in which the demand target is required in the input information as they are (for example, the above-mentioned scenes). Example of input pattern A4). In this case as well, the most suitable variation pattern may be selected based on the incidental information stored in the reception information storage unit 121 and / or the individual information stored in the individual information storage unit 124. In addition, each scene is processed by associating it with frequency information, and the frequency information associated with each scene is obtained from each estimated consumption point or area after the estimated consumption point or area is estimated from the estimated scene. It is tied to the area.

The point or area corresponding to the scene estimated by the estimation unit 132 may be specified based on the incidental information stored in the reception information storage unit 121 and / or the individual information stored in the individual information storage unit 124.

The scene estimated by the estimation unit 132 is a scene in which the current location or current location area when the input information is input, the movement point or the destination area estimated to move after the input information is input, or the like is not fixed; or the user's scene. It may be a scene where the home location or home area, the user's work / school location or the work / school area, etc. is fixed.

When the scene estimated by the estimation unit 132 is a scene where the location is fixed, a point or area corresponding to the estimated scene may be specified based on the attribute information of the user stored in the individual information storage unit 124. .. For example, when the scene estimated by the estimation unit 132 is the user's home location or home area, the point or area corresponding to the estimated scene can be specified from the user's home address stored in the individual information storage unit 124. .. For example, when the scene estimated by the estimation unit 132 is the user's workplace or school location or the workplace or school area, it corresponds to the scene estimated from the user's workplace or school address stored in the individual information storage unit 124. You can identify a point or area.

When the scene estimated by the estimation unit 132 is a scene in which the location is not fixed, based on the accompanying information stored in the reception information storage unit 121 and / or the user's behavior information stored in the individual information storage unit 124. You may identify a suitable point or area for the estimated scene. For example, when the scene estimated by the estimation unit 132 is the current location or the current location area when the input information is input, the information of the position or area at the time of input, which is the incidental information stored in the reception information storage unit 121, is used. The point or area corresponding to the estimated scene can be specified. For example, when the scene estimated by the estimation unit 132 is a movement point or a movement destination area estimated to move after inputting the input information, the movement history of the user or the search history of the user stored in the individual information storage unit 124. It is possible to predict the moving point or the moving destination area from and identify the point or area corresponding to the estimated scene.

For example, when the scene estimated by the estimation unit 132 is a moving point or a moving destination area, and a plurality of moving points or moving destination areas are predicted from the user's movement history or the user's search history, input. It is possible to select the most suitable moving point or destination area for information and identify the point or area corresponding to the estimated scene. For the prediction of the movement point or the movement destination area, for example, the behavior pattern can be analyzed from the movement history of the user, and the movement destination can be predicted based on the analyzed behavior pattern. Forecasting the travel point or destination area, for example, the travel destination can be predicted from the user's search history such as location search, map search, route search, and route search. Specifically, when the scene estimated by the estimation unit 132 is a movement point or a movement destination area, there is a user's search history consisting of a route search of "current location-> A station-> B intersection-> C center". In this case, it is predicted that there will be at least three destinations to move from now on: "A station", "B intersection", and "C center", but if the input information includes the character string "in front of the station", "A station" "Is selected, and a point or area corresponding to the estimated scene (for example," area around A station "," district including A station ", etc.) can be specified.

After specifying the point or area corresponding to the scene estimated as described above, the estimation unit 132 determines the estimated consumption point or area based on the reference geographic information stored in the geographic information storage unit 122 from the specified point or area. May be estimated. After specifying the point or area corresponding to the scene estimated as described above, the estimation unit 132 determines the specified point or area from the point information or area information of the reference geographic information stored in the geographic information storage unit 122. , Estimate the point or area corresponding to the determined reference geographic information as the estimated consumption point or area.

When the estimation unit 132 wishes to estimate the expected consumption area of the demand target for each area (when the area unit setting information is set), the estimation unit 132 is specified after specifying the point or area corresponding to the scene estimated as described above. The point or area is calculated from the point information or area information of the reference geographic information stored in the geographic information storage unit 122, and the appropriate area corresponding to the reference geographic information is estimated as the estimated consumption area based on the area unit setting information. ..

When the scene in which the demand target is required is estimated as one scene from one input information, the estimation unit 132 estimates one consumption prospective point or area. When the scene in which the demand target is required is estimated as two or more scenes from one input information, the estimation unit 132 can estimate two or more expected consumption points or areas together with the corresponding frequency information (for example, the above). In the example of the input pattern A2 of, when the user's current location is specified as A district, the destination is B district, the home is C district, and the workplace / school is D district, the expected consumption area is set to "A". It can be estimated that "district 11%, B district 5%, C district 72%, D district 12%").

The estimation unit 132 estimates the expected consumption point or area of the demand target from the input information, and then stores the obtained estimation result information in the estimation information storage unit 125. When two or more expected consumption points or areas are estimated for one input information (that is, when two or more scenes are estimated from the scene information database), the information stored in the estimation information storage unit 125 corresponds to the corresponding information. It may further include frequency information (ie, frequency information corresponding to demand situations corresponding to potential consumption points or areas). The information stored in the estimation information storage unit 125 may include other information. Other information may be information about the input pattern, information about the situation at the time of input including accompanying information, and / or information about the attributes of the user.

The estimation unit 132 may further optimize the scene information database stored in the scene information storage unit 123 based on the consumption trend of the demand target. By optimizing the scene information database, it can be a database showing scenes that match or approximate actual consumption trends. The scene information database may be updated regularly or irregularly depending on the purpose. When updating regularly, the frequency is 1 second, 10 seconds, 30 seconds, 1 minute, 10 minutes, 30 minutes, 1 hour, 4 hours, 6 hours, 12 hours. It may be every day, every day, every week, every month, every two months, every three months, every six months, every year, etc., and may be set as appropriate according to the purpose.

The estimation unit 132 may update the scene information database stored in the scene information storage unit 123 so as to match the actual consumption trend, or may update the scene information database so as to approach the actual consumption trend. In the scene information database, for example, for the input pattern A5, even if the combination of the demand required scene and the frequency information is set to "current location 100%" in the initial setting, the actual demand for the input information matching the input pattern A5. If the target consumption trend is "current location 11%, destination 5%, home 72%, work / school 12%", the estimation department 132 will change the combination of demand required scenes and frequency information from "current location 100%". It can be updated to "current location 11%, destination 5%, home 72%, work / school 12%".

The aggregation unit 133 aggregates the estimation result information stored in the estimation information storage unit 125 and creates the aggregation information. The aggregation method by the aggregation unit 133 may be appropriately determined from known methods according to the purpose, and is not particularly limited. The aggregation unit 133 may aggregate for each demand target. The aggregation unit 133 may aggregate for each demand target and create aggregation information for each demand target.

The aggregation unit 133 may aggregate by demand target and area. The aggregation unit 133 may aggregate for each demand target and for each area, and may create aggregate information for each area for each demand target. The aggregation unit 133 may aggregate by demand target and area, and may create aggregate information including the degree or frequency of consumption prospects for each area for each demand target.

The aggregation unit 133 may further aggregate by input pattern, user attribute, and / or situation at the time of input, based on other information stored in the estimation information storage unit 125. The aggregation unit 133 may aggregate by demand target, by input pattern, by user attribute and / or by situation at the time of input and by area.

The aggregation unit 133 may aggregate by demand target, input pattern, user attribute and / or by situation at the time of input and by area, and collectively create aggregate information for each area for each demand target. Aggregate information for each area may be created for each demand target, for each input pattern, for each user attribute and / or for each situation at the time of input.

The aggregation unit 133 aggregates by demand target, by input pattern, by user attribute and / or by situation at the time of input and by area, and aggregates by demand target and aggregate information including the degree or frequency of consumption prospect for each area. Or you may create aggregated information including the degree or frequency of expected consumption by area for each demand target, input pattern, user attribute and / or situation at the time of input.

The aggregation unit 133 may aggregate and create aggregated information including the degree or frequency of expected consumption based on the corresponding frequency information. The aggregation unit 133 may express the degree or frequency of expected consumption of the demand target by variables such as score, number of cases, and probability (for example, percentage). When the degree or frequency of expected consumption of the demand target is represented by a score and aggregated, the score may be generated by varying the weight according to the input pattern, the attribute of the user, and / or the situation at the time of input. For example, even if a minor who has no income inputs input information including information related to the demand target "luxury car", it is relatively unlikely that it will lead to the consumption of the demand target, but on the contrary, it is high. It is relatively likely that income earners will enter input information that includes information related to the demand target "luxury car", which will lead to consumption of the demand target. In such a case, for example, based on the information about the user's attribute, the score is "0.1" when the user's annual income is less than 3 million yen, the score is "1" when the user's annual income is 3 million yen or more and less than 6 million yen, and the user. If the annual income of the user is 6 million yen or more and less than 9 million yen, the score is "3", if the annual income of the user is 9 million yen or more and less than 15 million yen, the score is "5", and if the annual income of the user is 15 million yen or more, the score is "10". In addition, the score may be generated by varying the weight according to the user's income.

When two or more expected consumption points or areas are estimated for one input information, the aggregation unit 133 may aggregate using the corresponding frequency information. When two or more expected consumption points or areas are estimated for one input information, the aggregation unit 133 may aggregate each demand target by area according to the degree or frequency of expected consumption from the corresponding frequency information. ..

When two or more expected consumption points or areas are estimated for one input information, the aggregation unit 133 aggregates each demand target by area according to the degree or frequency of consumption prospect from the corresponding frequency information, and demand targets. Aggregate information including the degree or frequency of expected consumption for each area may be created for each area.

When the aggregation unit 133 estimates two or more expected consumption points or areas for one input information, the corresponding frequency information for each demand target, by input pattern, by user attribute, and / or by situation at the time of input. It is also possible to aggregate by area according to the degree or frequency of expected consumption, and to create aggregated information including the degree or frequency of expected consumption by area for each demand target.

When two or more expected consumption points or areas are estimated for one input information, the aggregation unit 133 cumulatively adds and aggregates the scores corresponding to the corresponding frequency information for each demand target for each demand target. Aggregate information including scores for each area may be created in.

When the aggregation unit 133 estimates two or more expected consumption points or areas for one input information, the corresponding frequency information for each demand target, by input pattern, by user attribute, and / or by situation at the time of input. The scores according to the above may be cumulatively added for each area and aggregated, and aggregated information including the scores for each area may be created for each demand target.

For example, for the same demand target A, there is one input pattern A1 "A district score 5 points, B district score 1 point, C district score 1 point, D district score 1 point", and input pattern A2 "A district score 1 point". , B district score 5 points, C district score 1 point, D district score 1 point ", the total is added up for each district, and the aggregated information" A district score 6 points, B district score 6 points " , C district score 2 points, D district score 2 points "may be created. For example, for the same demand target B, the input person is female and the input pattern B1 "A district score 1 point, B district score 1 point, C district score 1 point, D district score 10 points" is 1 case, and the input person is male. If there is one input pattern B1 "A district score 1 point, B district score 1 point, C district score 10 points, D district score 1 point", cumulative addition is performed for each district, and the aggregated information "A". You may create "district score 2 points, B district score 2 points, C district score 11 points, D district score 11 points".

The information aggregated by the aggregation unit 133 may be summarized in a table. The information aggregated by the aggregation unit 133 may be summarized as a distribution map, a distribution map, a bar graph, a pie graph, a band graph, a line graph, or the like. The information aggregated by the aggregation unit 133 may be summarized on a map, a satellite photograph, or an aerial photograph.

The aggregation unit 133 may aggregate in real time and create aggregated information, or may aggregate and create aggregated information by dividing it into arbitrary times or periods based on the time at the time of input. The time or period to divide for aggregation is 1 second, 10 seconds, 30 seconds, 1 minute, 10 minutes, 30 minutes, 1 hour, 4 hours, 6 hours, 12 hours, It may be every day, every week, every month, every two months, every three months, every six months, every year, etc., and any time or period may be set according to the purpose. .. The aggregation unit 133 stores the created aggregation information in the aggregation information storage unit 126.

The providing unit 134 provides the totaling information created by the totaling unit 133 to the business operator equipment 20 in response to a request from the business operator equipment 20.

[3. Configuration of terminal device 100]
Next, the configuration of the terminal device 100 according to the embodiment will be described with reference to FIG. FIG. 8 is a diagram showing a configuration example 100 of the terminal device according to the embodiment. As shown in FIG. 8, the terminal device 100 includes a communication unit 110, an input unit 120, an output unit 130, a physical sensor 140, and a control unit 150.

The communication unit 110 is realized by, for example, a NIC or the like. Then, the communication unit 110 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the information processing apparatus 10.

The input unit 120 is an input device that receives various operations from the user. For example, the input unit 120 is realized by a keyboard, a mouse, operation keys, or the like. The output unit 130 is a display device for displaying various information, that is, a screen. For example, the output unit 130 is realized by a liquid crystal display or the like. When a touch panel is adopted for the terminal device 100, the input unit 120 and the output unit 130 are integrated.

The physical sensor 140 is a sensor that detects various physical information of the terminal device 100, and is, for example, a gyro sensor, a temperature sensor, a volume sensor, a brightness sensor, an acceleration sensor, or the like. The physical sensor 140 may be a sensor that identifies the current position of the terminal device 100 by using a positioning system such as GPS.

The control unit 150 is realized by, for example, using a CPU, an MPU, or the like to execute various programs (corresponding to an example of an information display program) stored in the storage device inside the terminal device 100 using the RAM as a work area. .. For example, these various programs correspond to application programs called web browsers. Further, the control unit 150 is realized by an integrated circuit such as an ASIC or FPGA.

[4. Processing flow of terminal device 100]
With reference to FIG. 9, the information processing procedure executed by the terminal device 100 and the information processing device 10 in one embodiment will be described. FIG. 9 is a flowchart summarizing an example of the flow of information processing according to the embodiment.

In the example of FIG. 9, the terminal device 100 receives the input information input by the user from the input unit 120 (step S11). The terminal device 100 transmits the received input information from the output unit 130 to the information processing device 10 (step S12).

In the information processing apparatus 10, the reception unit 131 receives the input information and stores it in the reception information storage unit 121 (step S13).

When the input information stored in the reception information storage unit 121 includes the point area specific information (step S14: YES), the estimation unit 132 estimates the expected consumption point or area based on the point or area, and determines the demand target and the demand target. Information including the corresponding combination of expected consumption points or areas is stored in the estimated information storage unit 125 (step S15).

When the input information stored in the reception information storage unit 121 does not include the point area specific information (step S14: NO), the estimation unit 132 estimates the scene where the demand target is required from the input information (step S16). , It is estimated that the point or area corresponding to the estimated scene is the expected consumption point or area, and the estimation result information is stored in the estimation information storage unit 125 (step S17).

The aggregation unit 133 aggregates the estimation result information stored in the estimation information storage unit 125, creates aggregated information, and stores the aggregated information in the aggregated information storage unit 126 (step S18). The providing unit 134 provides the aggregated information stored in the aggregated information storage unit 126 to the operator apparatus 20 in response to a request from the operator apparatus 20 (step S19).

[5. others〕
[5-1. Modification example]
In the above, an example of the information processing system 1 has been described. However, the present invention is not limited to this. Of each of the processes described in the above embodiments, a part of the processes described as being automatically performed can be performed manually, or all or a part of the processes described as being performed manually. Can also be performed automatically by a known method. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown in the figure.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically in any unit according to various loads and usage conditions. Can be integrated and configured.

In addition, the above-described embodiments can be appropriately combined as long as the processing contents do not contradict each other.

[5-2. program〕
Further, the information processing device 10 and the terminal device 100 according to the above-described embodiment are realized by, for example, a computer 1000 having a configuration as shown in FIG. FIG. 10 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to the output device 1010 and the input device 1020, and the arithmetic unit 1030, the primary storage device 1040, the secondary storage device 1050, the output IF (Interface) 1060, the input IF 1070, and the network IF 1080 are connected by the bus 1090. Have.

The arithmetic unit 1030 operates based on a program stored in the primary storage device 1040 or the secondary storage device 1050, a program read from the input device 1020, or the like, and executes various processes. The primary storage device 1040 is a memory device that temporarily stores data used by the arithmetic unit 1030 for various operations such as RAM. Further, the secondary storage device 1050 is a storage device in which data used by the arithmetic unit 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), an HDD, a flash memory, or the like.

The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various information such as a monitor and a printer. For example, USB (Universal Serial Bus), DVI (Digital Visual Interface), and the like. It is realized by a connector of a standard such as HDMI (registered trademark) (High Definition Multimedia Interface). Further, the input IF 1070 is an interface for receiving information from various input devices 1020 such as a mouse, a keyboard, a scanner, and the like, and is realized by, for example, USB.

The input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like. Further, the input device 1020 may be an external storage medium such as a USB memory.

The network IF 1080 receives data from another device via the network N and sends it to the arithmetic unit 1030, and also transmits the data generated by the arithmetic unit 1030 to the other device via the network N.

The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040, and executes the loaded program.

For example, when the computer 1000 functions as the terminal device 100, the arithmetic unit 1030 of the computer 1000 realizes the function of the control unit 150 by executing the program loaded on the primary storage device 1040. When the computer 1000 functions as the information processing device 10, the arithmetic unit 1030 of the computer 1000 realizes the function of the control unit 13 by executing the program loaded on the primary storage device 1040.

[6. effect〕
As described above, the information processing apparatus 10 includes a reception unit 131 that receives input information including information related to the demand target input by the user, and an estimation unit 132 that estimates a consumption prospective point or area of the demand target from the input information. , Have.

Further, in the information processing apparatus 10 in one embodiment, when the input information includes the point area specifying information, the information processing apparatus 10 estimates the expected consumption point or area based on the point or area. Further, in the information processing apparatus 10 in one embodiment, when the estimation unit 132 does not include the point area specific information in the input information, the information processing apparatus 10 estimates a scene in which a demand target is required from the input information, and corresponds to the estimated scene. It is estimated that the point or area is the expected consumption point or area.

Further, in the information processing apparatus 10 in one embodiment, the estimation unit 132 determines a scene in which a demand target is required from the input information based on the information including the input pattern and the demand-required scene corresponding to the input pattern (that is, the scene information database). presume. Further, in the information processing apparatus 10 in one embodiment, the estimation unit 132 demands from the input information based on the combination of the input pattern and the fluctuation pattern and the information including the demand-required scene corresponding to the combination (that is, the scene information database). Estimate the scene where the target is needed.

Further, the information processing apparatus 10 in one embodiment is optimized by the estimation unit 132 further updating the information including the demand required scene (that is, the scene information database) based on the consumption trend of the demand target. Further, in the information processing apparatus 10 in one embodiment, the estimation unit 132 specifies a point or area corresponding to the estimated scene based on incidental information and / or individual information. Further, in the information processing apparatus 10 in one embodiment, the individual information is the user's attribute information and / or the user's behavior information.

Further, in the information processing apparatus 10 in one embodiment, the reception unit 131 receives the input information together with the accompanying information. Further, the information processing apparatus 10 in one embodiment further has an aggregation unit 133 that aggregates estimation result information and creates aggregated information. Further, in the information processing apparatus 10 in one embodiment, the aggregation unit 133 aggregates the estimation result information for each demand target and each area, and creates the aggregation information for each area for each demand target.

As a result of having the above-mentioned configuration, the information processing apparatus 10 can appropriately estimate the expected consumption point or area of the demand target from various input information.

Although some of the embodiments of the present application have been described in detail with reference to the drawings, these are examples, and various modifications are made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure column of the invention. , It is possible to carry out the present invention in other modified forms.

Further, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the distribution unit can be read as a distribution means or a distribution circuit.

1 Information processing system 10 Information processing device 11 Communication unit 12 Storage unit 121 Input information storage unit 122 Area information storage unit 123 Scene information storage unit 124 Individual information storage unit 125 Estimated information storage unit 126 Aggregate information storage unit 13 Control unit 131 Reception unit 132 Estimating unit 133 Totaling unit 134 Providing unit 20 Business operator equipment 100 Terminal equipment 120 Input unit 130 Output unit 140 Physical sensor 150 Control unit 1000 Computer 1010 Output device 1020 Input device 1030 Computing device,
1040 Primary storage 1050 Secondary storage 1060 Output IF
1070 input IF
1080 network IF
1090 bus

Claims (12)

A reception unit that accepts input information including information related to the demand target entered by the user,
An estimation unit that estimates the expected consumption point or area of the demand target from the input information,
Have,
The estimation unit is characterized in that it estimates a scene in which the demand target is required from the input information based on information including a pattern of the input information and a scene in which the demand target is required corresponding to the pattern. Processing equipment. The information processing according to claim 1, wherein when the input information includes information that can specify an estimated consumption point or area, the estimation unit estimates an estimated consumption point or area based on the point or area. Device. When the input information does not include information that can specify a consumption prospective point or area, the estimation unit estimates a scene in which the demand target is required from the input information, and determines a point or area corresponding to the estimated scene. The information processing apparatus according to claim 1 or 2, wherein the information processing apparatus is presumed to be an expected consumption point or area. The estimation unit is based on information including a combination of a pattern of the input information and a pattern in which the consumption tendency of the demand target is different and a scene in which the demand target is required corresponding to the combination, and the input information is described. The information processing apparatus according to any one of claims 1 to 3, wherein a scene in which a demand target is required is estimated. One of claims 1 to 4, wherein the estimation unit further optimizes by updating information including a scene in which the demand target is required based on the consumption trend of the demand target. The information processing device described in 1. The estimation unit is characterized in that a point or area corresponding to an estimated scene is specified based on information for identifying an input person, information on a situation at the time of input, and / or information on an individual user. The information processing apparatus according to any one of claims 1 to 5 . The estimation unit identifies a point or area corresponding to the estimated scene based on information for identifying the input person, information on the situation at the time of input, user attribute information, and / or user behavior information. The information processing apparatus according to claim 6 . The information processing apparatus according to any one of claims 1 to 7 , wherein the reception unit receives the input information together with information for identifying an input person and information on a situation at the time of input. Claims 1 to 1, further comprising an aggregation unit that aggregates information including a combination of the demand target and the expected consumption point or area of the demand target estimated by the estimation unit and creates aggregated information. The information processing apparatus according to any one of 8 . The aggregation unit aggregates information including a combination of the demand target and the expected consumption point or area of the demand target estimated by the estimation unit for each demand target and for each area, and for each demand target for each area. The information processing apparatus according to claim 9 , wherein the information processing apparatus is characterized in that aggregated information is created. It is an information processing method executed by an information processing device.
A reception process that accepts input information including information related to the demand target entered by the user,
An estimation process that estimates the expected consumption point or area of the demand target from the input information,
Including
The estimation step is information characterized in that the scene in which the demand target is required is estimated from the input information based on the information including the pattern of the input information and the corresponding scene in which the demand target is required. Processing method. A reception procedure for accepting input information including information related to the demand target entered by the user, and
An estimation procedure for estimating the expected consumption point or area of the demand target from the input information, and
Let the computer run
The estimation procedure is characterized in that the scene in which the demand target is required is estimated from the input information based on the information including the pattern of the input information and the corresponding scene in which the demand target is required. Processing program.

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