JP7509519B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

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

There is a known technology that provides a service that predicts the overall revenue of a movie theater from cinema advertising and notifies the movie theater of the predicted revenue (Reference 1). For example, there is a known technology that provides a service that notifies the movie theater of the revenue that the movie theater can obtain when the movie theater sets a new ticket price. There is also a known technology that determines a recommended price for a performance event ticket based on the attributes of the performance event ticket (Reference 2). There is also a known technology that calculates a second selling price based on a first selling price and fluctuations in inventory (Reference 3).

JP 2015-179472 A JP 2012-500429 A Patent No. 6516802

However, the above-mentioned conventional technologies are merely technologies related to determining ticket prices, and are not necessarily capable of properly determining information regarding ticket purchasing rights.

This application has been made in light of the above, and aims to appropriately determine information regarding ticket purchasing rights.

The information processing device according to the present application is characterized by having an acquisition unit that acquires user information about a user who wishes to purchase a ticket, and a determination unit that determines information about the right to purchase the ticket based on the user information acquired by the acquisition unit.

According to one aspect of the embodiment, it is possible to appropriately determine information regarding the right to purchase a ticket.

FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 2 is a diagram illustrating an example of information processing according to the embodiment. FIG. 3 is a diagram illustrating an example of information processing according to the embodiment. FIG. 4 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. FIG. 5 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. FIG. 6 is a diagram illustrating an example of the configuration of an information processing apparatus according to an embodiment. FIG. 7 is a diagram illustrating an example of an event information storage unit according to the embodiment. FIG. 8 is a diagram illustrating an example of a user information storage unit according to the embodiment. FIG. 9 is a diagram illustrating an example of a prediction information storage unit according to the embodiment. FIG. 10 is a diagram illustrating an example of a decision information storage unit according to the embodiment. FIG. 11 is a flowchart illustrating an example of information processing according to the embodiment. FIG. 12 is a diagram illustrating an example of information processing according to the modified example. FIG. 13 is a diagram illustrating an example of the configuration of an information processing system according to a modified example. FIG. 14 is a diagram illustrating an example of the configuration of an information processing device according to a modified example. FIG. 15 is a diagram illustrating an example of a bid information storage unit according to the modified example. FIG. 16 is a diagram illustrating an example of an entitlement determination information storage unit according to a modified example. FIG. 17 is a diagram illustrating an example of a right-granted user information storage unit according to a modified example. FIG. 18 is a flowchart showing an example of information processing according to the modified example. FIG. 19 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device.

Below, the information processing device, information processing method, and information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, information processing method, and information processing program according to the present application are not limited to these embodiments. In addition, the same parts in the following embodiments will be denoted by the same reference numerals, and duplicated descriptions will be omitted.

(Embodiment)
[1. An example of information processing]
1 shows a case where the information processing device 100 predicts a user's purchases at a target event (hereinafter, appropriately referred to as a "target event") based on the user's purchase history at past events. Also, FIG. 1 shows a case where the information processing device 100 determines information regarding the right to purchase tickets for the target event using information regarding the predicted user's purchases. Note that FIG. 1 shows a case where the target event is event A.

The ticket according to the embodiment may be any type of ticket for a specific event. For example, the ticket according to the embodiment may be a ticket for participating (entering) in a specific event. The event according to the embodiment may be any type of event, and is not limited to events held at venues such as baseball stadiums and movie theaters. For example, the event according to the embodiment may be an event held in a virtual space such as the Internet, and is not limited to events held in a physical space such as a venue. If the event according to the embodiment is held in a physical space such as a venue, the event according to the embodiment may be an event with seats or an event without the concept of seats. If the event is an event with seats, the event according to the embodiment may be an event with seat types or an event without seat types. In the example of FIG. 1, a ticket for an event without seat types will be described as an example. Hereinafter, an example of information processing according to the embodiment will be described with reference to FIG. 1.

The information processing device 100 acquires a ticket purchase request from user U1 (step S101). The information processing device 100 acquires a ticket purchase request for event A. The information processing device 100 acquires the ticket purchase request from user U1 transmitted from terminal device 10-1.

The information processing device 100 acquires user information on a user who wishes to purchase a ticket. The information processing device 100 may acquire any user information as long as the information is for predicting the user's purchases at the target event. For example, the information processing device 100 acquires user information including the user's purchase history at past events. As a specific example, the information processing device 100 acquires user information including the purchase history of goods purchased by the user at past events and food and drink at the venue. For example, the information processing device 100 acquires user information including the attribute information of the user. For example, the information processing device 100 acquires user information including the purchase history at past events of users similar to the user (hereinafter, appropriately referred to as "similar users"). For example, the information processing device 100 acquires user information on user U1.

The information processing device 100 predicts a predicted value for the user's purchases at the target event (hereinafter, appropriately referred to as "purchase prediction value") based on the user information (step S102). The purchase prediction value is the price at which the user is predicted to purchase at the target event. For example, the information processing device 100 predicts the purchase prediction value of user U1 at event A based on purchase history information LG1 indicating the purchase history of user U1 at past events. In the example shown in FIG. 1, the information processing device 100 generates prediction information ES1 indicating the purchase prediction value of user U1 at event A based on the purchase history information LG1. In addition, the information processing device 100 predicts the purchase prediction value of user U1 at event A to be 2,000 yen. For example, the information processing device 100 predicts the purchase prediction value of user U1 based on the purchase amount of 1,500 yen of user U1 at event IV1, which is a past event, and the purchase amount of 2,500 yen of user U1 at event IV2, which is a past event. Specifically, the information processing device 100 predicts the average of the purchase amount at event IV1 and the purchase amount at event IV2 as the predicted purchase value for user U1. This allows the information processing device 100 to estimate the revenue from merchandise purchases and food and drink at the venue for each user and reflect this in determining the ticket price.

The information processing device 100 determines information regarding the right to purchase a ticket for the target event (step S103). The information processing device 100 determines information regarding the right to purchase a ticket for event A when sold to user U1. The information processing device 100 determines information regarding the right to purchase a ticket for event A when sold to user U1 based on the purchase prediction value of user U1. For example, the information processing device 100 determines the price (selling price) of a ticket for event A when sold to user U1. Specifically, the information processing device 100 determines the price of a ticket for event A when sold to user U1 to be 8,000 yen. For example, the information processing device 100 determines the price of a ticket for event A based on the normal selling price (list price) of a ticket for event A and the purchase prediction value of user U1. For example, the information processing device 100 determines a variable price of a ticket for event A. For example, the information processing device 100 determines a variable price obtained by subtracting the purchase prediction value of user U1 from the normal selling price of a ticket for event A. For example, the information processing device 100 determines the variable price of a ticket for event A by subtracting the predicted purchase value of user U1, 2,000 yen, from the normal selling price of tickets for event A, 10,000 yen. In the example shown in FIG. 1, the information processing device 100 generates decision information SP1 indicating the price of event A when sold to user U1, based on the predicted purchase value indicated in the prediction information ES1 and the normal selling price stored in the event information storage unit 121.

The information processing device 100 provides a service of providing information on the price of tickets for the target event (step S104). For example, the information processing device 100 transmits information on the price of tickets for event A when sold to user U1 to the terminal device 10-1. The information processing device 100 provides information that the price of tickets for event A when sold to user U1 is 8,000 yen. The information processing device 100 provides the information shown in the decision information SP1.

The information processing device 100 acquires a ticket purchase request from user U2 (step S105). The information processing device 100 acquires the ticket purchase request from user U2 transmitted from terminal device 10-2.

The information processing device 100 predicts the purchase prediction value of user U2 at event A based on the user information on user U2 (step S106). For example, the information processing device 100 predicts the purchase prediction value of user U2 at event A based on purchase history information LG2 indicating the purchase history of user U2 at past events. In the example shown in FIG. 1, the information processing device 100 generates prediction information ES2 indicating the purchase prediction value of user U2 at event A based on the purchase history information LG2. Specifically, the information processing device 100 predicts the purchase prediction value of user U2 at event A to be 0 yen. That is, the information processing device 100 predicts that user U2 will not make a purchase at event A. For example, the information processing device 100 predicts the purchase prediction value of user U2 at event A to be 0 yen based on the purchase amount of user U2 at event IV5, which is a past event, and the purchase amount of user U2 at event IV6, which is a past event, to be 0 yen. For example, the information processing device 100 predicts the average of the purchase amount in event IV5 and the purchase amount in event IV6 as the purchase prediction value for user U2.

The information processing device 100 determines information regarding the right to purchase a ticket for event A when sold to user U2 (step S107). The information processing device 100 determines information regarding the right to purchase a ticket for event A when sold to user U2 based on the purchase prediction value of user U2. For example, the information processing device 100 determines the price (sales price) of the ticket for event A when sold to user U2. Specifically, the information processing device 100 determines the price of the ticket for event A when sold to user U2 to be 10,000 yen. For example, the information processing device 100 determines the price of the ticket for event A based on the normal sales price of the ticket for event A and the purchase prediction value of user U2. For example, the information processing device 100 determines the variable price of the ticket for event A when sold to user U2. For example, the information processing device 100 determines a variable price obtained by subtracting the purchase prediction value of user U2 from the normal sales price of the ticket for event A. For example, the information processing device 100 determines the variable price of a ticket for event A when sold to user U2 by subtracting 0 yen, which is the predicted purchase value for user U2, from the normal selling price of tickets for event A, which is 10,000 yen. In the example shown in FIG. 1, the information processing device 100 generates decision information SP2 indicating the price of a ticket for event A when sold to user U2, based on the predicted purchase value indicated in the prediction information ES2 and the normal selling price stored in the event information storage unit 121.

The information processing device 100 provides user U2 with a service of providing information regarding the price of tickets for the target event (step S108). The information processing device 100 transmits information regarding the price of tickets for event A when sold to user U2 to the terminal device 10-2. The information processing device 100 provides information that the price of tickets for event A when sold to user U2 is 10,000 yen. The information processing device 100 provides the information shown in decision information SP2.

2. Processing Variations
(2-1. Seat type)
In the example shown in Fig. 1, a case where the ticket price for the entire event is determined because there are no seat types is shown, but if there are seat types, the information processing device 100 may determine the ticket price for each seat type. For example, the information processing device 100 may perform the same process as in Fig. 1 using information on the normal selling price of tickets for each seat type. For example, the information processing device 100 may determine a variable price obtained by subtracting a user's predicted purchase value from the normal selling price of tickets for each seat type. Note that seat types may be determined for each area of the event venue.

Figure 2 shows the types of seats for a given event. The stadium shown in Figure 2 includes an S seat with rank S, which is the highest grade in the stadium, an A seat with rank A, which is the next highest grade after rank S, a B seat with rank B, which is the next highest grade after rank A, a C seat with rank C, which is the next highest grade after rank B, and a D seat with rank D, which is the lowest grade in the stadium. In addition, it is assumed that a normal selling price is determined in advance for each rank. For example, when the information processing device 100 acquires a purchase request for a ticket with rank S from a given user, the information processing device 100 may determine a variable price obtained by subtracting the purchase prediction value of the given user from the normal selling price of the ticket with rank S as the selling price of the ticket with rank S when sold to the given user. For example, when the information processing device 100 acquires a purchase request for a ticket with rank A from a given user, the information processing device 100 may determine a variable price obtained by subtracting the purchase prediction value of the given user from the normal selling price of the ticket with rank A as the selling price of the ticket with rank A when sold to the given user.

(2-2. Seats)
The information processing device 100 may determine the price of the ticket for each seat. For example, the information processing device 100 may perform the same process as in FIG. 1 using information on the normal selling price of the ticket for each seat. For example, the information processing device 100 may determine a variable price obtained by subtracting the user's predicted purchase value from the normal selling price of the ticket for each seat. FIG. 3 shows seating for a given event. The seating shown in FIG. 3 includes seats S1 to S8, which are front row seats close to the stage, and seats S9 to S16, which are back row seats. It is also assumed that seats S4 and S5 are in the center of the front row seats, and seats S12 and S13 are in the center of the back row seats. It is also assumed that a normal selling price is set in advance for each seat. For example, when the information processing device 100 acquires a purchase request for a ticket for seat S4 from a given user, it may determine a variable price obtained by subtracting the predetermined user's predicted purchase value from the normal selling price of the ticket for seat S4 as the selling price of the ticket for seat S4 when sold to the given user. For example, when the information processing device 100 receives a purchase request for a ticket for seat S16 from a specific user, it may determine the selling price of the ticket for seat S16 when sold to the specific user to be a variable price obtained by subtracting the predicted purchase value of the specific user from the regular selling price of the ticket for seat S16.

(2-3. Purchase prediction value)
In the example shown in FIG. 1, the information processing device 100 predicts the average value of the purchase history of the user in past events as the user's purchase prediction value, but the information processing device 100 may predict the user's purchase prediction value using various other methods. For example, when the amount of information of the user's purchase history is less than a predetermined threshold, the information processing device 100 may predict the user's purchase prediction value based on the user's attribute information. For example, when the average purchase amount of men in their twenties who have the same attributes as the user is 3,000 yen, the information processing device 100 may predict the average amount of 3,000 yen as the user's purchase prediction value. In this case, the information processing device 100 may predict the amount after a predetermined discount is applied from the average amount as the user's purchase prediction value. For example, the information processing device 100 may predict 27,000 yen, which is a 10% discount on the average amount of 3,000 yen, as the user's purchase prediction value. In this way, when the amount of information of the user's purchase history is equal to or greater than a predetermined threshold, the information processing device 100 may predict the user's purchase prediction value based on the user's purchase history, and when the amount of information of the user's purchase history is less than the predetermined threshold, the information processing device 100 may predict the user's purchase prediction value based on the user's attribute information. Furthermore, when the amount of information in the user's purchase history is less than a predetermined threshold, the information processing device 100 may predict the user's purchase prediction value based on a predetermined function based on the user's attribute information and the user's purchase history. Furthermore, when the amount of information in the user's purchase history is less than a predetermined threshold, the information processing device 100 may predict the user's purchase prediction value as a predetermined amount. For example, when the amount of information in the user's purchase history is less than a predetermined threshold, the information processing device 100 may predict the user's purchase prediction value as 0 yen. For example, when the average purchase amount based on the user's purchase history is equal to or less than a predetermined threshold, the information processing device 100 may predict the amount after inflating a predetermined amount as the user's purchase prediction value. For example, when the average purchase amount based on the user's purchase history is 0 yen, the information processing device 100 may predict the amount after inflating a predetermined amount as the user's purchase prediction value. For example, the information processing device 100 may predict the maximum or minimum value of the purchase amount based on the user's purchase history as the user's purchase prediction value. For example, the information processing device 100 may predict the maximum or minimum purchase amount based on the user's purchase history within a predetermined period as the user's purchase predicted value. For example, the information processing device 100 may predict the maximum or minimum purchase amount based on the user's purchase history for past events held during the same period as the target event as the user's purchase predicted value. For example, the information processing device 100 may predict the maximum or minimum purchase amount based on the user's purchase history for past events held during the same spring, summer, fall, and winter periods as the target event as the user's purchase predicted value.

(2-4. Purchasing)
The purchase according to the embodiment is not limited to the purchase of goods or food and drink at the venue, but may be any purchase related to the profits of the event. For example, the purchase according to the embodiment may be the use of lockers or toilets at the venue.

3. Configuration of Information Processing System
The information processing system 1 shown in Fig. 4 will be described. As shown in Fig. 4, the information processing system 1 includes a terminal device 10 and an information processing device 100. The terminal device 10 and the information processing device 100 are connected to each other via a predetermined communication network (network N) so as to be able to communicate with each other by wire or wirelessly. Fig. 4 is a diagram showing an example of the configuration of the information processing system according to the embodiment. Note that the information processing system 1 shown in Fig. 4 may include a plurality of terminal devices 10 and a plurality of information processing devices 100.

The terminal device 10 is an information processing device used by a user. The terminal device 10 may be any device that can realize the processing in the embodiment. The terminal device 10 may also be a device such as a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, or a PDA. In the example shown in FIG. 1, the terminal device 10 is a smartphone.

The information processing device 100 is used to determine information related to the right to purchase a ticket. The information processing device 100 is, for example, an information processing device such as a PC or a WS (Work Station), and performs processing based on information transmitted from a terminal device 10 or the like via a network N.

4. Configuration of terminal device
Next, the configuration of the terminal device 10 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the configuration of the terminal device 10 according to the embodiment. As shown in Fig. 5, the terminal device 10 has a communication unit 11, an input unit 12, an output unit 13, and a control unit 14.

(Communication unit 11)
The communication unit 11 is realized by, for example, a network interface card (NIC) etc. The communication unit 11 is connected to a predetermined network N by wire or wirelessly, and transmits and receives information to and from the information processing device 100 etc. via the predetermined network N.

(Input unit 12)
The input unit 12 accepts various operations from users. In the example shown in Fig. 1, the input unit 12 accepts various operations from users U1 and U2. For example, the input unit 12 may accept various operations from users via a display surface using a touch panel function. The input unit 12 may also accept various operations from buttons provided on the terminal device 10 or a keyboard or mouse connected to the terminal device 10.

(Output unit 13)
The output unit 13 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various information. For example, the output unit 13 outputs information regarding the price of tickets for the target event.

(Control unit 14)
The control unit 14 is, for example, a controller, and is realized by a CPU (Central Processing Unit), MPU (Micro Processing Unit), etc., executing various programs stored in a storage device inside the terminal device 10 using a RAM (Random Access Memory) as a working area. For example, the various programs include application programs installed in the terminal device 10. For example, the various programs include an application program that displays information about ticket prices for a target event. The control unit 14 is also realized by an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 5, the control unit 14 has a transmission unit 141 and a reception unit 142, and realizes or executes the information processing functions described below.

(Transmitter 141)
The transmission unit 141 provides various information to an external information processing device. The transmission unit 141 transmits various information to an external information processing device. The transmission unit 141 transmits various information to another information processing device such as the information processing device 100. For example, the transmission unit 141 transmits a ticket purchase request from a user.

(Receiving unit 142)
The receiving unit 142 receives various information. The receiving unit 142 receives various information from an external information processing device. The receiving unit 142 receives various information from another information processing device such as the information processing device 100. For example, the receiving unit 142 receives a service providing information on tickets for a target event. For example, the receiving unit 142 receives information on the price of tickets for the target event.

5. Configuration of information processing device
Next, the configuration of the information processing device 100 according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 6, the information processing device 100 has a communication unit 110, a storage unit 120, and a control unit 130. Note that the information processing device 100 may have an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100, and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC etc. The communication unit 110 is connected to a network N by wire or wirelessly, and transmits and receives information to and from the terminal device 10 etc. via the network N.

(Memory unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 6, the storage unit 120 has an event information storage unit 121, a user information storage unit 122, a prediction information storage unit 123, and a decision information storage unit 124.

The event information storage unit 121 stores information about a target event. For example, the event information storage unit 121 stores the normal selling price of tickets for the target event. FIG. 7 shows an example of the event information storage unit 121 according to an embodiment. As shown in FIG. 7, the event information storage unit 121 has items such as "target event ID," "event name," "venue," and "normal selling price (list price)."

"Target event ID" indicates identification information for identifying the target event. "Event name" indicates the name of the target event. For example, "event name" indicates that the name of the target event identified by target event IV11 is event A. "Venue" indicates the venue where the target event will be held. For example, "Venue" indicates that the target event identified by target event IV11 will be held at facility A. "Normal selling price (list price)" indicates the normal selling price (list price) of tickets for the target event. For example, "Normal selling price (list price)" indicates that the normal selling price of tickets for the target event identified by target event IV11 is 10,000 yen.

The user information storage unit 122 stores user information. FIG. 8 shows an example of the user information storage unit 122 according to the embodiment. As shown in FIG. 8, the user information storage unit 122 has items such as "user ID" and "user information."

"User ID" indicates identification information for identifying a user. "User information" indicates user information. As shown in FIG. 8, "user information" may have items such as "attribute information" and "purchase history". "Attribute information" indicates attribute information of a user. In the example shown in FIG. 8, conceptual information such as "attribute information #1" and "attribute information #2" is stored in "attribute information", but in reality, information such as the user's age and gender is stored. "Purchase history" indicates the purchase history of a user in past events. As shown in FIG. 8, "purchase history" may have items such as "past event ID" and "purchase amount". "Past event ID" indicates identification information for identifying an event that was held in the past. "Purchase amount" indicates the purchase amount of the user in the corresponding past event. For example, "purchase amount" indicates that the purchase amount of user U1 in the past event identified by past event IV1 is 1,500 yen.

The prediction information storage unit 123 stores prediction information regarding user purchases in a target event. FIG. 9 shows an example of the prediction information storage unit 123 according to an embodiment. As shown in FIG. 9, the prediction information storage unit 123 has items such as "user ID" and "prediction information."

"User ID" indicates identification information for identifying a user. "Prediction information" indicates prediction information regarding purchases by the user in the target event. As shown in FIG. 9, "prediction information" may have items such as "target event ID" and "purchase prediction value." "Target event ID" indicates identification information for identifying the target event. "Purchase prediction value" indicates the user's purchase prediction value in the target event. For example, "purchase prediction value" indicates that the purchase prediction value of user U1 in the target event identified by target event IV11 is 2,000 yen.

The decision information storage unit 124 stores information regarding the right to purchase tickets for the target event. For example, the decision information storage unit 124 stores information regarding the price of tickets for the target event determined for each user. For example, the decision information storage unit 124 stores the variable price of tickets for the target event for each user. Here, FIG. 10 shows an example of the decision information storage unit 124 according to the embodiment. As shown in FIG. 10, the decision information storage unit 124 has items such as "user ID" and "decision information".

"User ID" indicates identification information for identifying a user. "Determined information" indicates information regarding the right to purchase tickets for the determined target event. For example, "Determined information" indicates information regarding the variable price of tickets for the target event. As shown in FIG. 10, "Determined information" may have items such as "Target event ID" and "Variable price". "Target event ID" indicates identification information for identifying the target event. "Variable price" indicates the variable price of tickets for the target event determined for each user. For example, "Variable price" indicates that the variable price for user U1 for the target event identified by target event IV11 is 8,000 yen.

(Control unit 130)
The control unit 130 is a controller, and is realized, for example, by a CPU, an MPU, or the like, executing various programs stored in a storage device inside the information processing device 100 using a RAM as a working area. The control unit 130 is also a controller, and is realized, for example, by an integrated circuit such as an ASIC or an FPGA.

As shown in FIG. 6, the control unit 130 has an acquisition unit 131, a prediction unit 132, a determination unit 133, and a provision unit 134, and realizes or executes the information processing action described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 6, and may be other configurations as long as they perform the information processing described below.

(Acquisition unit 131)
The acquisition unit 131 acquires various pieces of information. The acquisition unit 131 acquires various pieces of information from an external information processing device. The acquisition unit 131 acquires various pieces of information from another information processing device such as the terminal device 10.

The acquisition unit 131 acquires various pieces of information from the storage unit 120. The acquisition unit 131 acquires various pieces of information from the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, and the decision information storage unit 124.

The acquisition unit 131 stores the acquired various information in the storage unit 120. The acquisition unit 131 stores the various information in the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, and the decision information storage unit 124.

The acquisition unit 131 acquires various information predicted and determined by other functional configurations.

The acquisition unit 131 acquires a ticket purchase request from a user. The acquisition unit 131 acquires a ticket purchase request sent from the terminal device 10.

The acquisition unit 131 acquires user information about a user who wishes to purchase a ticket. The acquisition unit 131 acquires user information including the user's purchase history in past events. The acquisition unit 131 acquires user information including the user's attribute information. The acquisition unit 131 acquires user information including the purchase history in past events of similar users who are similar to the user.

The acquisition unit 131 acquires information related to the target event. The acquisition unit 131 acquires information related to the regular selling price of tickets for the target event. The acquisition unit 131 acquires information related to the regular selling price of tickets for each seat or each seat type.

(Prediction Unit 132)
The prediction unit 132 predicts various pieces of information. The prediction unit 132 calculates various pieces of information. The prediction unit 132 predicts and calculates various pieces of information from the storage unit 120. For example, the prediction unit 132 predicts and calculates various pieces of information from the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, and the decision information storage unit 124.

The prediction unit 132 predicts and calculates various information acquired and determined by other functional configurations. The prediction unit 132 also predicts and calculates various information based on various information acquired and determined by other functional configurations.

The prediction unit 132 predicts a predicted value regarding purchases for the user in the target event. The prediction unit 132 predicts a predicted purchasing value for the user in the target event. The prediction unit 132 predicts a predicted purchasing value for the target event for each user. The prediction unit 132 predicts the predicted purchasing value based on user information. For example, the prediction unit 132 predicts the predicted purchasing value by averaging the purchase amounts for the user's past events.

(Determination unit 133)
The determination unit 133 determines various information. The determination unit 133 calculates various information. The determination unit 133 determines and calculates various information from the storage unit 120. For example, the determination unit 133 determines and calculates various information from the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, and the determined information storage unit 124.

The determination unit 133 determines various pieces of information acquired and predicted by other functional configurations. The determination unit 133 also determines various pieces of information based on various pieces of information acquired and predicted by other functional configurations.

The determination unit 133 determines information regarding the right to purchase tickets for the target event. The determination unit 133 determines information regarding the right to purchase tickets for the target event based on user information. For example, the determination unit 133 determines information regarding the right to purchase tickets for the target event based on the user's purchasing history. For example, the determination unit 133 determines information regarding the right to purchase tickets for the target event based on the user's attribute information. For example, the determination unit 133 determines information regarding the right to purchase tickets for the target event based on the purchasing history of similar users.

The determination unit 133 determines information regarding the right to purchase tickets for the target event using the purchase prediction value for the target event. The determination unit 133 determines information regarding the right to purchase tickets for the target event based on the purchase prediction value predicted by the prediction unit 132.

The determination unit 133 determines the price of tickets for the target event when sold to a specific user based on the user information of the specific user. For example, the determination unit 133 determines the price of tickets for the target event when sold to user U1 based on the user information of user U1.

The determination unit 133 reduces the price of tickets for the target event when sold to a corresponding user as the predicted purchasing amount of the user in the target event increases. For example, the determination unit 133 reduces the price of tickets for the target event when sold to user U1 as the predicted purchasing amount of user U1 in the target event increases.

The determination unit 133 determines the variable price obtained by subtracting a discount value based on the user's purchase amount for the target event from the normal selling price of the ticket for the target event as the price of the ticket for the target event when sold to the corresponding user. For example, the determination unit 133 determines the variable price obtained by subtracting a discount value based on the user U1's purchase amount for the target event from the normal selling price of the ticket for the target event as the price of the ticket for the target event when sold to user U1.

When it is predicted that the user will not make a purchase for the target event, the determination unit 133 determines the price of the ticket for the target event when sold to the corresponding user to be the normal selling price of the ticket for the target event. For example, when it is predicted that the user U1 will not make a purchase for the target event, the determination unit 133 determines the price of the ticket for the target event when sold to the user U1 to be the normal selling price of the ticket for the target event.

(Providing Unit 134)
The providing unit 134 provides various information to an external information processing device. The providing unit 134 transmits various information to an external information processing device. The providing unit 134 notifies the external information processing device of various information. The providing unit 134 distributes various information to the external information processing device. The providing unit 134 provides various information to other information processing devices such as the terminal device 10.

The provision unit 134 provides various information acquired, predicted, and determined by other functional configurations.

The provision unit 134 provides a service of providing information regarding the right to purchase tickets for the target event. The provision unit 134 provides a service of providing information regarding the price of tickets for the target event. The provision unit 134 provides information regarding the price of tickets for the target event to a corresponding user.

[6. Information processing flow]
Next, the procedure of information processing by the information processing system 1 according to the embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the procedure of information processing by the information processing system 1 according to the embodiment.

As shown in FIG. 11, the information processing device 100 determines whether or not a ticket purchase request from the user has been acquired (step S201). If the information processing device 100 has not acquired a ticket purchase request from the user (step S201; NO), it waits until it acquires a ticket purchase request from the user. In addition, when the information processing device 100 acquires a ticket purchase request from the user, it calculates a purchase prediction value for the user's purchase at the target event based on the corresponding user's purchase history (step S202). Based on the calculated purchase prediction value, the information processing device 100 determines the price of the ticket for the target event when sold to the corresponding user (step S203). For example, the information processing device 100 determines the price of the ticket for the target event to be a variable price obtained by subtracting the calculated purchase prediction value from the normal selling price of the ticket for the target event. The information processing device 100 provides information on the determined ticket price for the target event to the corresponding user (step S204).

7. Modifications
The information processing system 1 according to the embodiment described above may be implemented in various different forms other than the above embodiment. Therefore, other embodiments of the information processing system 1 will be described below. Note that the description of the same points as those in the embodiment shown in FIG. 1 will be omitted as appropriate. Note that in the example of FIG. 12, a ticket for an event without seat types will be described as an example. Also, in FIG. 12, a ticket for a specified seat will be described as an example.

Figure 12 shows a case where information processing device 100A determines information regarding a user's predicted expected value (hereinafter, appropriately referred to as "predicted expected value") when purchasing a ticket for the target event based on the user's bid amount for the ticket for the target event. Also, Figure 12 shows a case where information processing device 100A determines a right-granting user to be granted the right to purchase a ticket for the target event based on information regarding the user's expected value. An example of information processing related to the modified example will be described below with reference to Figure 12.

The information processing device 100A acquires bidding information regarding user U1's bid for tickets to the target event (step S301). The information processing device 100A acquires the bid amount of user U1 for tickets to the target event. The information processing device 100A acquires information regarding the bid by user U1 transmitted from terminal device 10-1. In FIG. 12, the information processing device 100A acquires information indicating that user U1 has bid 9,000 yen for a ticket for seat SH21 for event A.

Based on the same process as step S102, the information processing device 100A predicts the purchase prediction value of user U1 for the target event (step S302). In FIG. 12, the information processing device 100A predicts the purchase prediction value of user U1 based on purchase history information LG21. In FIG. 12, the information processing device 100A generates prediction information ES21 indicating the purchase prediction value of user U1 based on the purchase history information LG21. Specifically, the information processing device 100A predicts the purchase prediction value of user U1 to be 2,000 yen.

The information processing device 100A determines the predicted expected value of the user U1 in the target event (step S303). The information processing device 100A determines the predicted expected value of the user U1 in the target event based on the purchase prediction value of the user U1 in the target event and the bid information of the user U1 for the tickets of the target event. Specifically, the information processing device 100A determines the sum of the purchase prediction value of the user U1 of 2,000 yen and the bid amount of the user U1 of 9,000 yen as the predicted expected value of the user U1. In FIG. 12, the information processing device 100A determines the predicted expected value of the user U1 to be 11,000 yen. In FIG. 12, the information processing device 100A generates right grant determination information VS21, which is information for determining a user to be granted the right to purchase tickets for the target event (hereinafter, referred to as "right granted user" as appropriate), based on the prediction information ES21 indicating the purchase prediction value of the user U1 and the bid information BD21 indicating the bid amount of the user U1.

The information processing device 100A acquires the bid information of user U2 for tickets to the target event (step S304). The information processing device 100A acquires the bid amount of user U2 for tickets to the target event. The information processing device 100A acquires the bid information of user U2 transmitted from terminal device 10-2. In FIG. 12, the information processing device 100A acquires information that user U2 has bid 10,000 yen for tickets to seat SH21 for event A.

The information processing device 100A predicts the predicted purchasing value of user U2 for the target event (step S305). In FIG. 12, the information processing device 100A predicts the predicted purchasing value of user U2 based on the purchasing history information LG22. In FIG. 12, the information processing device 100A generates prediction information ES22 indicating the predicted purchasing value of user U2 based on the purchasing history information LG22. Specifically, the information processing device 100A predicts the predicted purchasing value of user U2 to be 0 yen.

The information processing device 100A determines the predicted expected value of user U2 for the target event based on the predicted purchase value of user U2 for the target event and the bid information of user U2 for tickets to the target event. Specifically, the information processing device 100A determines the sum of user U2's predicted purchase value of 0 yen and user U2's bid amount of 10,000 yen as the predicted expected value of user U2. In FIG. 12, the information processing device 100A determines the predicted expected value of user U2 to be 10,000 yen. In FIG. 12, the information processing device 100A generates right grant determination information VS22 based on prediction information ES22 indicating user U2's predicted purchase value and bid information BD22 indicating user U2's bid amount.

The information processing device 100A determines a user to be granted rights to a ticket for the target event based on the predicted expected value of user U1 and the predicted expected value of user U2. The information processing device 100A determines a user to be granted rights to a ticket for the target event by comparing the predicted expected value of user U1 and the predicted expected value of user U2. In FIG. 12, the information processing device 100A determines user U1 as the granted rights user because the predicted expected value of user U1, 11,000 yen, is greater than the predicted expected value of user U2, 10,000 yen. In FIG. 12, the information processing device 100A determines user U1 as the successful bidder for a ticket for seat SH21 for event A.

The information processing device 100A provides information to the user U1 that the user U1 has been determined to be the right-granted user (step S308). For example, the information processing device 100A provides information that the user U1 has won a ticket for seat SH21 for event A. The information processing device 100A transmits a service for providing information regarding the granting of rights to the terminal device 10-1.

The information processing device 100A provides user U2 with information that another user has been selected as the right-granting user (step S309). For example, the information processing device 100A provides information that user U1 was not successful in bidding for a ticket for seat SH21 for event A. The information processing device 100A transmits a service for providing information regarding the granting of rights to the terminal device 10-2.

8. Configuration of Information Processing System
An information processing system 1A shown in FIG. 13 will be described. As shown in FIG. 13, the information processing system 1A includes a terminal device 10 and an information processing device 100A. The terminal device 10 and the information processing device 100A are connected to each other via a predetermined communication network (network N) so as to be able to communicate with each other by wire or wirelessly. FIG. 13 is a diagram showing an example of the configuration of an information processing system according to an embodiment. Note that the information processing system 1A shown in FIG. 13 may include a plurality of terminal devices 10 and a plurality of information processing devices 100A.

The information processing device 100A is used to determine information related to the right to purchase a ticket. The information processing device 100A is, for example, an information processing device such as a PC or a WS (Work Station), and performs processing based on information transmitted from a terminal device 10 or the like via a network N.

9. Configuration of terminal device
(Transmitter 141)
The transmission unit 141 transmits various information to other information processing devices such as the information processing device 100A. For example, the transmission unit 141 transmits information related to bidding for tickets to the target event. For example, the transmission unit 141 transmits information related to the bid amount for tickets to the target event.

(Receiving unit 142)
The receiving unit 142 receives various information from other information processing devices such as the information processing device 100A. For example, the receiving unit 142 receives a service that provides information regarding the granting of rights to a ticket for a target event. For example, the receiving unit 142 receives information regarding the granting of rights to a ticket for a target event.

10. Configuration of information processing device
Next, the configuration of the information processing device 100A according to the embodiment will be described with reference to Fig. 14. Fig. 14 is a diagram showing an example of the configuration of the information processing device 100A according to the embodiment. As shown in Fig. 14, the information processing device 100A has a communication unit 110, a storage unit 120A, and a control unit 130. Note that the information processing device 100A may have an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100A, and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

(Memory unit 120A)
The storage unit 120A is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 14, the storage unit 120A has an event information storage unit 121, a user information storage unit 122, a prediction information storage unit 123, a bid information storage unit 124A, a right granting determination information storage unit 125A, and a right granting user information storage unit 126A.

The bid information storage unit 124A stores information about user bids for tickets to a target event. FIG. 15 shows an example of the bid information storage unit 124A according to an embodiment. As shown in FIG. 15, the bid information storage unit 124A has items such as "user ID" and "bid information."

"User ID" indicates identification information for identifying a user. "Bid information" indicates information related to a user's bid. "Bid information" may have items such as "seat" and "bid amount." "Seat" indicates identification information for identifying a seat. "Bid amount" indicates the bid amount placed by a user. For example, "bid amount" indicates that the bid amount by user U1 for the seat identified by seat SH21 is 9,000 yen.

The right-granting information storage unit 125A stores information for determining which right-granting users will be granted the right to purchase tickets for the target event. FIG. 16 shows an example of the right-granting information storage unit 125A according to the embodiment. As shown in FIG. 16, the right-granting information storage unit 125A has items such as "user ID" and "right-granting information."

"User ID" indicates identification information for identifying a user. "Rights granting determination information" indicates information for determining the rights granting user. "Rights granting determination information" may have items such as "target event ID", "seat", and "predicted expected value". "Target event ID" indicates identification information for identifying the target event. "Seat" indicates identification information for identifying a seat. "Predicted expected value" indicates the predicted user's expected value when purchasing a ticket for the target event. For example, "predicted expected value" indicates that the predicted expected value of user U1 for seat SH21 for target event IV11 is 11,000 yen.

The entitled user information storage unit 126A stores information about entitled users of tickets for a target event. FIG. 17 shows an example of the entitled user information storage unit 126A according to an embodiment. As shown in FIG. 17, the entitled user information storage unit 126A has fields such as "Target event ID," "Event name," "Venue," "Seat," and "Entitled user (winning bidder)."

"Target event ID" indicates identification information for identifying the target event. "Event name" indicates the name of the target event. "Venue" indicates the venue where the target event will be held. "Seat" indicates identification information for identifying seats for the target event. "Rights granted user (successful bidder)" indicates the rights granted user (successful bidder) who is granted the right to purchase a ticket. For example, "Rights granted user (successful bidder)" indicates that the rights granted user for the ticket for the seat identified by seat SH21 is user U1.

(Control unit 130)
The control unit 130 is a controller, and is realized, for example, by a CPU, an MPU, or the like, executing various programs stored in a storage device inside the information processing device 100A using a RAM as a working area.

(Acquisition unit 131)
The acquisition unit 131 acquires various information from the storage unit 120A. The acquisition unit 131 acquires various information from the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, the bid information storage unit 124A, the right granting determination information storage unit 125A, and the right granted user information storage unit 126A.

The acquisition unit 131 stores the acquired various information in the storage unit 120A. The acquisition unit 131 stores the various information in the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, the bid information storage unit 124A, the right granting decision information storage unit 125A, and the right granting user information storage unit 126A.

The acquisition unit 131 acquires information regarding user bids. The acquisition unit 131 acquires the user's bid amount for tickets to the target event. The acquisition unit 131 acquires information regarding bids from multiple users.

The acquisition unit 131 acquires a predicted expected value of a user predicted when a ticket for a target event is purchased. The acquisition unit 131 acquires predicted expected values of multiple users. The acquisition unit 131 acquires other predicted expected values of other users.

(Determination unit 133)
The determination unit 133 determines various information from the storage unit 120A. For example, the determination unit 133 determines various information from the event information storage unit 121, the user information storage unit 122, the prediction information storage unit 123, the bid information storage unit 124A, the right grant determination information storage unit 125A, and the right granted user information storage unit 126A.

The determination unit 133 determines the user's predicted expected value. The determination unit 133 determines the user's predicted expected value based on the user's bid amount. The determination unit 133 determines the sum of the user's predicted purchase value and the bid amount as the user's predicted expected value.

The determination unit 133 determines the right-granted user. The determination unit 133 determines the right-granted user for the ticket of the target event.

The determination unit 133 determines the entitled user in an auction format. The determination unit 133 determines the entitled user based on the bid amount. The determination unit 133 determines the entitled user using a predicted expected value of the user based on the bid amount and user information. The determination unit 133 determines the entitled user using a predicted expected value predicted when the user purchases a ticket based on the bid amount and user information. The determination unit 133 determines the entitled user using a predicted expected value determined from the user's predicted purchase value based on the user information and the bid amount. The determination unit 133 determines the entitled user using a predicted expected value that is the sum of the predicted purchase value and the bid amount. The determination unit 133 determines the entitled user based on the predicted expected values of multiple users. The determination unit 133 determines the entitled user based on a comparison of the predicted expected value of the user with other predicted expected values of other users. If the predicted expected value of the user is greater than the other predicted expected values of other users, the determination unit 133 determines the user as the entitled user.

(Providing Unit 134)
The providing unit 134 provides a service of providing information regarding the granting of rights to a ticket for a target event. The providing unit 134 provides information regarding the granting of rights to a ticket for a target event.

[11. Information Processing Flow]
Next, the procedure of information processing by the information processing system 1A according to the embodiment will be described with reference to Fig. 18. Fig. 18 is a flowchart showing the procedure of information processing by the information processing system 1A according to the embodiment.

As shown in FIG. 18, the information processing device 100A determines whether or not the user's bid amount for the ticket has been acquired (step S401). If the information processing device 100A has not acquired the user's bid amount for the ticket (step S401; NO), the information processing device 100A waits until the user's bid amount for the ticket is acquired. In addition, when the information processing device 100A acquires the user's bid amount for the ticket, the information processing device 100A calculates a purchase prediction value for the user's purchase in the target event based on the corresponding user's purchase history (step S402). Based on the calculated purchase prediction value and the acquired bid amount, the information processing device 100A calculates a predicted expected value for the user's expected value when purchasing the corresponding ticket (step S403). Based on the calculated predicted expected value, the information processing device 100A determines the user to whom the right of the corresponding ticket will be granted (step S404). The information processing device 100A provides information regarding the determined right grant to the corresponding user (step S405).

12. Processing Variations
(12-1. Seat)
In the example shown in FIG. 12, the price of a ticket when there is a concept of a seat is shown as an example. FIG. 12 shows a case where the information processing device 100 determines a right-granting user of a ticket for seat SH21 of event A based on the bid amount for the ticket for seat SH21 of event A. Here, the information processing device 100 may determine a right-granting user using a price when there is no concept of a seat. For example, in step S301, the information processing device 100 may obtain a bid amount for a ticket when there is no concept of a seat. For example, in step S303, the information processing device 100 may calculate a predicted expected value of a user predicted when purchasing a ticket when there is no concept of a seat. For example, in step S307, the information processing device 100 may determine a right-granting user of a ticket when there is no concept of a seat.

(12-2. Seat type)
In the example shown in FIG. 12, the ticket price in the case where there is no seat type is shown as an example, but the information processing device 100 may determine the right-granting user using the ticket price in the case where there is a seat type. For example, in step S301, the information processing device 100 may acquire the bid amount for the ticket of each seat type for each seat type. For example, when a user makes a bid for a seat of rank S, the information processing device 100 may acquire the bid amount for the ticket of rank S. For example, in step S303, the information processing device 100 may calculate the predicted expected value of the user predicted when purchasing a ticket of each seat type for each seat type. For example, in step S307, the information processing device 100 may determine the right-granting user of the ticket of each seat type for each seat type. In addition, the information processing device 100 may allocate the seats corresponding to the seat type to the determined right-granting user. For example, when a certain right-granting user makes a bid for two tickets of rank S, the information processing device 100 may provide two tickets of rank S.

13. Effects
As described above, the information processing device 100 according to the embodiment includes the acquisition unit 131 and the determination unit 133. The acquisition unit 131 acquires user information related to a user who wishes to purchase a ticket. The determination unit 133 determines information related to the right to purchase a ticket based on the user information acquired by the acquisition unit 131.

As a result, the information processing device 100 according to the embodiment can appropriately determine information regarding ticket purchasing rights. Furthermore, the information processing device 100 according to the embodiment can appropriately reflect user information in determining the ticket price. For example, the information processing device 100 according to the embodiment can estimate revenue from merchandise purchases and venues for each user, and appropriately reflect this in determining the ticket price.

The acquisition unit 131 also acquires user information including the user's purchasing history for past events. The determination unit 133 also determines information regarding the right to purchase tickets based on the user's purchasing history.

This allows the information processing device 100 according to the embodiment to appropriately determine information regarding ticket purchasing rights based on the user's purchasing history.

The acquisition unit 131 also acquires user information including user attribute information. The determination unit 133 also determines information regarding the right to purchase tickets based on the attribute information.

This allows the information processing device 100 according to the embodiment to appropriately determine information regarding ticket purchasing rights based on the user's attribute information.

In addition, the acquisition unit 131 acquires user information including the purchase history of similar users who are similar to the user in past events. In addition, the determination unit 133 determines information regarding the right to purchase tickets based on the purchase history of the similar users.

As a result, the information processing device 100 according to the embodiment can appropriately determine information regarding ticket purchasing rights based on the purchasing history of similar users.

The determination unit 133 also determines information regarding the right to purchase a ticket using a predicted value for purchases at the event corresponding to the user's ticket based on the user information.

As a result, the information processing device 100 according to the embodiment can appropriately determine information regarding ticket purchasing rights based on predictions regarding purchases at the event.

The information processing device 100 according to the embodiment also has a prediction unit that predicts a predicted value based on user information. The determination unit 133 also determines information regarding the right to purchase a ticket based on the predicted value predicted by the prediction unit 132.

As a result, the information processing device 100 according to the embodiment can appropriately determine information regarding ticket purchasing rights based on predictions regarding purchases at the event.

The determination unit 133 also determines the price of the ticket when sold to the user based on the user information.

This allows the information processing device 100 according to the embodiment to appropriately reflect user information in determining the ticket price.

In addition, the determination unit 133 lowers the price of the ticket when sold to the user as the predicted user purchase amount for the event corresponding to the ticket increases.

As a result, the information processing device 100 according to the embodiment can provide cheaper tickets to users who have a large predicted purchasing amount based on the prediction of purchasing at the event.

The determination unit 133 also determines the variable price, obtained by subtracting a discount amount based on the user's purchase amount for the event corresponding to the ticket from the regular selling price of the ticket, as the price of the ticket when sold to the user.

As a result, the information processing device 100 according to the embodiment can appropriately determine the price of the ticket based on the predicted purchase amount of the user.

In addition, if it is predicted that the user will not purchase the ticket for the event corresponding to the ticket, the determination unit 133 determines the price of the ticket when sold to the user to be the regular selling price of the ticket.

As a result, the information processing device 100 according to the embodiment can appropriately determine the price of the ticket based on the predicted purchase amount of the user.

The determination unit 133 also determines the right-granting users to whom the right to purchase tickets will be granted based on the user information.

This allows the information processing device 100 according to the embodiment to appropriately reflect user information in determining the user to be granted rights.

The determination unit 133 also determines the users to whom rights will be granted through an auction format.

As a result, the information processing device 100 according to the embodiment can appropriately determine the users to whom rights will be granted through an auction format.

The acquisition unit 131 also acquires the bid amount for the ticket by the user. The determination unit 133 also determines the user to whom rights will be granted based on the bid amount.

This allows the information processing device 100 according to the embodiment to appropriately determine the right-granting user based on the user's bid amount.

The determination unit 133 also determines the user to whom rights will be granted using a predicted expected value predicted if a user purchases a ticket based on the bid amount and user information.

As a result, the information processing device 100 according to the embodiment can appropriately determine the user to whom rights will be granted based on the predicted expected value.

In addition, the determination unit 133 determines the user to whom rights will be granted using a predicted expected value determined from a predicted value for purchases at an event corresponding to the user's ticket based on the user information and the bid amount.

As a result, the information processing device 100 according to the embodiment can appropriately determine the user to whom rights will be granted based on the predicted expected value.

In addition, the determination unit 133 determines the user to whom rights will be granted using the predicted expected value, which is the sum of the predicted value and the bid amount.

As a result, the information processing device 100 according to the embodiment can appropriately determine the user to whom rights will be granted based on the predicted expected value.

The acquisition unit 131 also acquires other predicted expected values of other users. The determination unit 133 also determines the right-granting user based on a comparison between the predicted expected value of the user and the other predicted expected values of the other users.

As a result, the information processing device 100 according to the embodiment can appropriately determine the user to whom rights will be granted based on a comparison with the predicted expected values of other users.

In addition, if the user's predicted expected value is greater than other predicted expected values of other users, the determination unit 133 determines the user to be a right-granted user.

As a result, the information processing device 100 according to the embodiment can appropriately determine the user to whom rights will be granted based on a comparison with the predicted expected values of other users.

14. Hardware Configuration
Moreover, the terminal device 10 and the information processing device 100 (or the information processing device 100A) according to the above-described embodiments are realized, for example, by a computer 1000 having a configuration as shown in FIG. 19. FIG. 19 is a hardware configuration diagram showing an example of a computer that realizes the functions of the terminal device 10 and the information processing device 100 (or the information processing device 100A). The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD 1400, a communication interface (I/F) 1500, an input/output interface (I/F) 1600, and a media interface (I/F) 1700.

The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400, and controls each component. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started, and programs that depend on the hardware of the computer 1000, etc.

HDD 1400 stores programs executed by CPU 1100 and data used by such programs. Communication interface 1500 receives data from other devices via a specified communication network and sends it to CPU 1100, and transmits data generated by CPU 1100 to other devices via the specified communication network.

The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input/output interface 1600. The CPU 1100 acquires data from the input devices via the input/output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input/output interface 1600.

The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

For example, when the computer 1000 functions as the terminal device 10 and information processing device 100 (or information processing device 100A) according to the embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control units 14 and 130 by executing programs loaded onto the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a specified communication network.

15. Other
Furthermore, among the processes described in the above embodiments and modifications, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

The above-described embodiments and variations can be combined as appropriate to the extent that they do not cause inconsistencies in the processing content.

Although several embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the disclosure section of the invention.

The above-mentioned "section, module, unit" can be read as "means" or "circuit." For example, an acquisition unit can be read as an acquisition means or an acquisition circuit.

REFERENCE SIGNS LIST 1 Information processing system 1A Information processing system 10 Terminal device 100 Information processing device 100A Information processing device 110 Communication unit 120 Storage unit 120A Storage unit 121 Event information storage unit 122 User information storage unit 123 Prediction information storage unit 124 Decision information storage unit 124A Bidding information storage unit 125A Rights grant decision information storage unit 126A Rights grant user information storage unit 130 Control unit 131 Acquisition unit 132 Prediction unit 133 Decision unit 134 Provision unit N Network

Claims (10)

an acquisition unit that acquires user information related to a user who wishes to purchase a ticket, the user information including purchase history of similar users similar to the user in past events;
a determination unit that determines a price of the ticket when sold to the user as information regarding the right to purchase the ticket based on the user information acquired by the acquisition unit, and determines a right-granting user to be granted the right to purchase the ticket as information regarding the right to purchase the ticket based on a comparison between a predicted expectation value of the user based on the user information and other predicted expectation values of other users ;
An information processing device comprising: The determination unit is
The information processing device according to claim 1 , wherein the price of the ticket when sold to the user is reduced as the predicted purchase amount of the user for the event corresponding to the ticket increases. The determination unit is
The information processing device according to claim 1 or claim 2, characterized in that a variable price obtained by subtracting a discount amount based on the user's purchase amount for the event corresponding to the ticket from the regular selling price of the ticket is determined as the price of the ticket when sold to the user. The determination unit is
The information processing device according to any one of claims 1 to 3, characterized in that if it is predicted that the user will not make a purchase at the event corresponding to the ticket, the price of the ticket when sold to the user is determined to be the normal selling price of the ticket. The determination unit is
5. The information processing apparatus according to claim 1, wherein the user to whom the right is to be granted is determined in an auction format. The acquisition unit is
obtaining a bid amount for the ticket by the user;
The determination unit is
The information processing device according to any one of claims 1 to 5, characterized in that the entitled user is determined using a predicted expected value predicted when the user purchases the ticket based on the bid amount and the user information, the predicted expected value being determined from a predicted value for purchases of the user in the event corresponding to the ticket based on the user information and the bid amount. The determination unit is
The information processing apparatus according to claim 6 , wherein the user to be granted the right is determined using the predicted expected value, which is a sum of the predicted value and the bid amount. The determination unit is
2 . The information processing apparatus according to claim 1 , wherein when the predicted expected value of the user is greater than the predicted expected value of the other user, the user is determined to be the right-granting user. 1. A computer-implemented information processing method, comprising:
An acquisition step of acquiring user information related to a user who wishes to purchase a ticket, the user information including purchase history of similar users similar to the user in past events;
a determination step of determining a price of the ticket when sold to the user as information regarding the right to purchase the ticket based on the user information acquired in the acquisition step, and determining a right-granting user to be granted the right to purchase the ticket as information regarding the right to purchase the ticket based on a comparison between a predicted expectation value of the user based on the user information and other predicted expectation values of other users;
13. An information processing method comprising: An acquisition step of acquiring user information related to a user who wishes to purchase a ticket, the user information including purchase history of similar users similar to the user in past events;
a determination step of determining a price of the ticket when sold to the user as information regarding the right to purchase the ticket based on the user information acquired by the acquisition step, and determining a right-granting user to be granted the right to purchase the ticket as information regarding the right to purchase the ticket based on a comparison between a predicted expectation value of the user based on the user information and other predicted expectation values of other users;
An information processing program characterized by causing a computer to execute the above.

Images