JP7724644B2 - 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.

Technology is known that determines the blend of a pre-prepared pet food based on the association of nutritional information with pet information about a first pet, such as age, weight, and sex, and second pet information, such as ingredients, food form, and flavor.

Special table 2016-518818 publication

However, the above-mentioned conventional technology simply determines the pet food blend based on the association between various pet information and nutritional information. In recent years, pet foods have become more diverse, making it desirable to meet not only the specific needs of pets but also the diverse needs of pet owners. There is room for improvement in this regard.

This application was made in light of the above, and aims to provide information on appropriate pet food that reflects the preferences of pet owners.

The information processing device according to the present application is characterized by comprising a reception unit that receives preference information relating to the preferences of pet owners and pet information relating to the pets, a determination unit that determines pet food to recommend to the owner based on the preference information and the pet information, and a provision unit that provides the owner with information relating to the pet food determined by the determination unit.

According to one aspect of the embodiment, it is possible to provide information on appropriate pet food that reflects the owner's preferences.

FIG. 1 is a diagram illustrating an example of information processing executed by an information processing apparatus according to an embodiment. FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. FIG. 3 is a diagram illustrating an example of an owner information storage unit according to the embodiment. FIG. 4 is a diagram illustrating an example of a pet information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a product information storage unit according to the embodiment. FIG. 6 is a flowchart illustrating an example of the flow of a providing process executed by the information processing apparatus according to the embodiment. FIG. 7 is a flowchart showing an example of the flow of the update process executed by the information processing apparatus according to the embodiment. FIG. 8 is a diagram illustrating an example of a hardware configuration.

At least the following points become clear from the description in this specification and the accompanying drawings.

An information processing device comprising: a reception unit that receives preference information regarding the preferences of pet owners and pet information regarding the pets; a determination unit that determines pet food to recommend to the owner based on the preference information and the pet information; and a provision unit that provides the owner with information regarding the pet food determined by the determination unit.

Such an information processing device accepts preference information indicating, for example, the owner's thoughts about the health of their pet, the owner's thoughts about the pet's preferences, and the owner's preference for cherishing contact with their pet. The information processing device also accepts pet information including attribute information related to the pet's attributes, such as the pet's age, and intake information indicating the pet food intake status. The information processing device then determines the pet food to recommend to the owner based on the preference information and the pet information. The information processing device then provides the owner with information about the determined pet food. This makes it possible to provide information about appropriate pet food that reflects the owner's preferences.

For example, pet owners may want their pets to live long, healthy lives, but may not be able to determine which pet food will be beneficial to their pet's health. Even if owners are able to select an appropriate pet food that is thought to be beneficial to their pet's health, they may have difficulty selecting a pet food because they do not know whether their pet will eat it. In response to these issues, information processing devices can provide information about appropriate pet foods that reflect the owner's preferences, thereby providing peace of mind to owners by suggesting pet foods that their pets will enjoy eating and that are suitable for their pets.

For example, even if you feed your pet its favorite pet food every day, there are cases where the pet may not eat it depending on its mood, or may stop eating it because it gets tired of the food. In response to this, an information processing device can provide information about appropriate pet foods, suggesting pet foods that will reduce the risk of your pet not eating, and helping your pet live a long and healthy life.

The information processing device also inputs the preference information and the pet information and uses a learning model to determine the pet food, outputting a score indicating the degree to which a specific pet food is optimal.

This type of information processing device determines the pet food using a learning model that inputs preference information and pet information and outputs a score indicating the degree to which a specific pet food is optimal, making it possible to determine information regarding appropriate pet food that reflects the owner's preferences.

The information processing device also receives preference information regarding the pet's health as the preference information, and determines the pet food to recommend to the owner based on the preference information regarding the pet's health and the pet information.

This type of information processing device determines the pet food to recommend to the owner based on pet health preference information and pet information, making it possible to determine information about appropriate pet food that reflects the owner's preferences.

The information processing device also receives preference information regarding the pet's preferences as the preference information, and determines the pet food to recommend to the owner based on the preference information regarding the pet's preferences and the pet information.

This type of information processing device determines the pet food to recommend to the owner based on preference information that focuses on the pet's preferences and pet information, making it possible to determine information about appropriate pet food that reflects the owner's preferences.

The information processing device also receives owner information, which is information about the owner and is different from the preference information, and determines the pet food to recommend to the owner based on the owner information, the preference information, and the pet information.

This type of information processing device determines the pet food to recommend to the owner based on owner information, preference information, and pet information, making it possible to determine information about appropriate pet food that reflects the owner's preferences.

The information processing device also receives feeding information regarding the feeding method for the pet as the owner information, and determines the pet food to recommend to the owner based on the feeding information, the preference information, and the pet information.

This type of information processing device determines the pet food to recommend to the owner based on feeding information, preference information, and pet information, making it possible to determine information about appropriate pet food that reflects the owner's preferences.

The information processing device also receives, as the owner information, external environment information relating to the environment around the place where the owner lives or the area in which the owner is active, and determines the pet food to recommend to the owner based on the external environment information, the preference information, and the pet information.

This type of information processing device determines the pet food to recommend to the owner based on external environment information, preference information, and pet information, making it possible to determine information about appropriate pet food that reflects the owner's preferences.

In addition, the information processing device provides the pet owner with information about the pet food, as well as related information that is related to the pet food.

This type of information processing device provides pet owners with information about pet food as well as related information that is relevant to the pet food, making it possible to provide appropriate information about pet food and related information that reflects the owner's preferences.

The information processing device also provides the pet owner with at least one of the following related information: information about the ingredients of the pet food, information about the nutritional components contained in the pet food, information about additives added to the pet food, information about the country of origin of the ingredients of the pet food, and information about the place where the pet food was produced.

This type of information processing device provides the pet owner with at least one of the following related information: information about the ingredients of the pet food, information about the nutritional components contained in the pet food, information about the additives added to the pet food, information about the country of origin of the ingredients of the pet food, and information about the place where the pet food was produced. This makes it possible to provide the pet owner with information about appropriate pet food that reflects the owner's preferences, as well as related information.

Below, an example of a form for implementing an information processing device, an information processing method, and an information processing program (hereinafter referred to as an "embodiment") will be described in detail with reference to the drawings. Note that the information processing device, information processing method, and information processing program are not limited to this embodiment. Furthermore, identical components in the following embodiments will be assigned the same reference numerals, and duplicate explanations will be omitted.

[Embodiment]
1. An example of information processing performed by the information processing device
An example of information processing executed by an information processing apparatus 100 according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram illustrating an example of information processing executed by the information processing apparatus 100 according to an embodiment.

In the example of Figure 1, an example is described in which the information processing device 100 determines the pet food to recommend to the owner based on the answer to a question notified via chat. In this case, the information processing device 100 accepts owner information, pet information, etc. by accepting the answer from the owner to the question notified via chat.

In the example of Figure 1, it is assumed that a specific messaging application is pre-installed on the terminal device 10 used by the owner. In this case, the terminal device 10 can send and receive messages via chat using the specific messaging application.

As shown in FIG. 1, the information processing device 100 accepts a chat (message) from the terminal device 10 via a predetermined message application (step S1). In this case, the information processing device 100 can send and receive messages via chat with the terminal device 10 via the predetermined message application. For example, the information processing device 100 accepts a message request in response to an operation from the owner in response to a message displayed on the chat.

Next, the information processing device 100 notifies the user of a question via chat (step S2). For example, the information processing device 100 may notify the user of a question about the owner's preferences or about the pet.

To give a more specific example, the information processing device 100 may notify the owner of questions about their preferences, such as whether the owner is concerned about their pet's health or what the owner pays attention to when feeding their pet pet food.

In addition, the information processing device 100 may notify the owner of questions regarding their preferences, such as questions about what they pay attention to when selecting pet food, whether they select pet food primarily with the pet's health in mind or whether they select pet food primarily with the pet's preferences in mind, and whether they value interacting with their pet. In addition to questions regarding the owner's preferences, the information processing device 100 may also notify questions regarding the owner's age, gender, number of pets, family composition, etc.

The information processing device 100 also notifies the user of questions about pets, such as questions about the pet's attributes. For example, the information processing device 100 notifies the user of questions about the pet's type, age, sex, weight, body conditioning score, whether the pet has been neutered, preferences, etc.

The information processing device 100 also notifies the user of questions about the pet, such as questions about the food the pet has eaten. For example, the information processing device 100 notifies the user of questions about the date and time the food was eaten, or the time of meal if the pet eats twice a day, the food, the amount eaten, etc.

Then, the information processing device 100 accepts answers to the questions via chat (step S3). For example, the information processing device 100 accepts answers to each question by selecting from options notified along with the question. The information processing device 100 also accepts answers to each question entered by the owner in free-form format.

The information processing device 100 then determines the pet food to recommend to the owner based on the answers (step S4). For example, the information processing device 100 inputs preference information received in response to the questions and pet information, and determines the pet food to recommend to the owner using a learning model that outputs a score indicating the degree to which a specific pet food is optimal.

The learning model pre-learns the relationship between a given owner's preference information, pet information, and the pet food selected by the owner, and when preference information and pet information are input, it outputs a score indicating the degree to which the given pet food is optimal.

To give a more specific example, if the preference information indicates that the owner is health-conscious and the pet information indicates that the pet weighs more than pets of the same age and breed, the information processing device 100 inputs this preference information and the pet information into the learning model. Then, if the pet food for which the score output by the learning model is equal to or greater than a predetermined threshold is pet food "ABC," the information processing device 100 determines pet food "ABC" as the pet food to recommend to the owner. Here, pet food "ABC" is a low-calorie pet food that can prevent weight gain when consumed by a pet.

Furthermore, if the preference information indicates that the owner is an owner who is interested in pet preferences and the pet information indicates that the pet's weight is standard, the information processing device 100 inputs this preference information and the pet information into the learning model. Then, if the pet food for which the score output by the learning model is equal to or greater than a predetermined threshold is pet food "XYZ," the information processing device 100 determines pet food "XYZ" as the pet food to recommend to the owner. Here, pet food "XYZ" is made using domestic beef as an ingredient, and has a good texture and a fragrant aroma that stimulates the pet's appetite.

Then, the information processing device 100 provides information about pet food via chat (step S5). For example, the information processing device 100 provides the terminal device 10 with a message including advertising content about pet food "ABC" and information for redirecting the user to an internet shopping site where pet food "ABC" can be purchased. This allows the information processing device 100 to provide information about appropriate pet food that reflects the owner's preferences.

Furthermore, the information processing device 100 may acquire the pet's intake status of pet food "ABC" after step S5 is executed and a predetermined period of time has passed. For example, the information processing device 100 may notify questions regarding the date and time when pet food "ABC" was consumed, the amount of pet food "ABC" eaten, etc. Then, the information processing device 100 acquires the pet food "ABC" intake status by accepting answers to these questions.

The information processing device 100 may then update the parameters of the learning model based on the intake status of pet food "ABC." For example, the information processing device 100 may update the parameters of the learning model by learning the relationship between the preference information of the owner who purchased pet food "ABC" and information regarding the amount eaten, included in the pet's intake status of pet food "ABC."

For example, the information processing device 100 performs a learning process for the learning model using a technique such as backpropagation (backpropagation method). In this case, the information processing device 100 adjusts the weight values that are taken into account when values are transmitted between nodes through the learning process. In this way, the information processing device 100 learns through a process such as backpropagation, which corrects parameters so as to reduce the error between the output (first output and second output) in the learning model and the correct answer (classification label) corresponding to the input. The information processing device 100 also updates the parameters of the learning model by performing a process such as backpropagation so as to minimize a predetermined loss function.

Furthermore, when the intake amount indicated by the intake status of pet food "ABC" is below a predetermined threshold, the information processing device 100 may use the learning model to provide the owner with information about similar pet foods that are different from pet food "ABC."

In the prior art, pet food blends are simply determined based on the association between various pet information and nutritional information. As a result, there are limitations to addressing not only the specific needs of pets, but also the diverse needs of pet owners. As such, conventional pet food selection methods do not take into account the pet food preferences of pet owners, and as a result, it is sometimes difficult for owners to be satisfied with the pet food suggested. Furthermore, when feeding their pets pet food that the owner is not satisfied with, the owner may wonder whether the pet food they are currently feeding is the optimal pet food.

The information processing device 100 according to the embodiment therefore provides information about pet food that is determined based on preference information and pet information and is recommended to the owner. This allows the information processing device 100 to provide information about appropriate pet food that reflects the owner's preferences. In other words, the information processing device 100 can provide information about pet food that is customized based on the owner's preferences. In this way, the information processing device 100 can respond to not only the specific needs of pets, but also the diverse needs of owners. Therefore, the information processing device 100 can provide information about pet food that the owner is satisfied with, giving the owner a sense of security when feeding their pet.

2. Configuration of the information processing system
Next, the configuration of an information processing system 1 according to an embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the information processing system 1 according to an embodiment. As shown in Fig. 2, 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 network N so as to be able to communicate with each other via a wired or wireless connection. Note that the information processing system 1 shown in Fig. 2 may include a plurality of terminal devices 10 and a plurality of information processing devices 100.

The terminal device 10 according to the embodiment is an information processing device used by a user to access content such as web content or application content displayed in a browser. For example, the terminal device 10 may be a desktop personal computer (PC), a notebook PC, a tablet terminal, a mobile phone, or a personal digital assistant (PDA).

The information processing device 100 according to the embodiment is an information processing device capable of communicating with various devices via a network N such as the Internet, and is realized, for example, by a server device or a cloud system. For example, the information processing device 100 is connected to various other devices via the network N so that it can communicate with them.

3. Configuration of information processing device
The configuration of the information processing device 100 according to the embodiment will be described with reference to Fig. 2. Fig. 2 shows an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 2, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(Regarding the communication unit 110)
The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to a network N by wire or wirelessly, and transmits and receives information to and from various other devices.

(Regarding the storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 has an owner information storage unit 121, a pet information storage unit 122, a learning model 123, and a product information storage unit 124.

(Regarding the owner information storage unit 121)
The owner information storage unit 121 according to the embodiment stores various information related to the owner. Here, Fig. 3 shows an example of the owner information storage unit 121 according to the embodiment. In the example shown in Fig. 4, the owner information storage unit 121 has items such as "owner ID (Identifier)" and "owner information." For example, the "owner information" includes "preference information,""age,""gender,""number of pets,""familycomposition,""residentialinformation," and "external environment information."

"Owner ID" is an identifier that identifies the owner. "Preference information" is information related to the owner's preferences associated with the "Owner ID." For example, preference information may be preference information related to the pet's health or preference information related to the pet's preferences.

"Age" is information about the age of the owner associated with the "Owner ID." "Gender" is information about the gender of the owner associated with the "Owner ID." "Number of pets" is information about the number of pets kept by the owner associated with the "Owner ID."

"Family structure" is information about the owner's family associated with the "Owner ID." For example, the family structure may be a nuclear family or an extended family. The family structure may also include information about family members. For example, the family structure may include information about family members such as a husband and wife, older brothers, and younger brothers.

"Residence information" is information about the owner's residence associated with the "owner ID." For example, residence information includes information about the owner's address, and information about the owner's residence type, such as rental or detached. Residence information may also include information about the size of the residence, such as the land area. In other words, residence information includes information indicating the size of the owner's living space.

"External environment information" is information about the environment associated with the "owner ID." For example, external environment information is information about the environment around the place where the owner lives, or information about the environment in the owner's area of activity. More specific examples include information about the weather, temperature, room temperature, humidity, etc. around the place where the owner lives or in the area where the owner is active.

"Feeding information" is information about the feeding method for the pet associated with the "owner ID." For example, feeding information includes information about whether the pet is fed using a designated container or whether the owner feeds the pet directly by hand, how many times the pet is fed per day, the time the pet is fed, and the amount of food fed at one time.

For example, in Figure 3, "U1" identified by the owner ID has preference information of "UI1", age of "UA1", and gender of "US1". Furthermore, "U1" has the number of pets "UN1", family structure of "UF1", residence information of "UL1", and external environment information of "UE1".

In the example shown in Figure 3, preference information, etc. is expressed using abstract codes such as "UI1," but preference information, etc. may also be numerical values, information related to character strings, or the file format of a file containing preference information, etc.

(Regarding the pet information storage unit 122)
The pet information storage unit 122 according to the embodiment stores various pieces of information related to pets. An example of the pet information storage unit 122 according to the embodiment is shown in Fig. 4. In the example shown in Fig. 4, the pet information storage unit 122 includes items such as "pet ID,""ownerID," and "pet information."

For example, "pet information" includes "attribute information" and "intake information." For example, "attribute information" includes "species," "age," "sex," "weight," "body conditioning score," "neutered or not," and "preferences." For example, "intake information" includes "date and time," "food," and "amount eaten."

"Pet ID" is an identifier that identifies the pet. "Owner ID" is an identifier that identifies the owner associated with the "Pet ID." "Type" is information about the type of pet associated with the "Pet ID." "Age" is information about the age of the pet associated with the "Pet ID."

"Gender" is information about the gender of the pet associated with the "Pet ID." "Weight" is information about the weight of the pet associated with the "Pet ID." "Body Conditioning Score" is information about the body conditioning score associated with the "Pet ID." For example, the body conditioning score (BCS) is an index that classifies a pet's body shape using a five-point scale, such as BCS1 to BCS5. For example, BCS1 is "thin." BCS2 is "slightly thin." BCS3 is "ideal." BCS4 is "slightly obese." BCS5 is "obese."

"Neutered or not" is information about whether the pet associated with the "Pet ID" has been neutered or not. "Preferences" is information about the preferences of the pet associated with the "Pet ID".

"Date and time" is information about the date and time when the pet associated with the "Pet ID" ate food. "Food" is information about the food ingested by the pet associated with the "Pet ID". "Amount eaten" is information about the amount of food ingested by the pet associated with the "Pet ID".

For example, in Figure 4, "P1" identified by the pet ID has an owner ID of "UI1", a type of pet of "PT1", an age of "PG1", a sex of "PS1", and a weight of "PW1". Furthermore, "P1" has a body conditioning score of "PB1", a neuter status of "yes", and a preference of "PI1".

Furthermore, for "P1", the date and time is "DA1", the food is "FO1", and the amount eaten is "FA1".

In the example shown in Figure 5, the type etc. is expressed using abstract codes such as "PT1", but the type etc. may also be a numerical value, information about a character string, or the file format of a file containing the type etc. The intake information may also include information about the drink consumed by the pet. In this case, the intake information may further include the "date and time the drink was consumed", the "drink", and the "amount consumed".

(Regarding the product information storage unit 124)
The product information storage unit 124 according to the embodiment stores various information related to products. An example of the product information storage unit 124 according to the embodiment is shown in Fig. 5. In the example shown in Fig. 5, the product information storage unit 124 has fields such as "product ID,""type,""product," and "quantity."

"Product ID" is an identifier that identifies a product. "Type" is information about the type of product associated with the "Product ID." For example, type is information about the animal species, age, product form (e.g., portioned), and product packaging (e.g., canned, pouched, etc.). "Product" is information about the product associated with the "Product ID." "Quantity" is information about the quantity of the product associated with the "Product ID." For example, if the product is pet food, the quantity of the product is the number of grams of pet food.

For example, in Figure 5, "M1" identified by the product ID has a type of "MT1", a product of "MC1", and a quantity of "MA1". Note that in the example shown in Figure 5, the type, etc. is expressed as an abstract code such as "MT1", but the type, etc. may also be a numerical value, information related to a character string, or a file format containing information related to the type, etc.

(Regarding the control unit 130)
The control unit 130 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) using RAM as a work area to execute various programs (examples of information processing programs) stored in a storage device inside the information processing device 100. The control unit 130 is also a controller, and is realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 2, the control unit 130 has a reception unit 131, a determination unit 132, a provision unit 133, an acquisition unit 134, and an update unit 135, and realizes or executes the information processing functions and actions described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 2, and may be other configurations that perform the information processing described below. Furthermore, the connection relationships between the processing units in the control unit 130 are not limited to the connection relationships shown in FIG. 2, and may be other connection relationships.

(Regarding the Reception Unit 131)
The reception unit 131 receives various types of information and various requests. Specifically, the reception unit 131 receives chat messages from the terminal device 10 via a predetermined message application. In this case, the reception unit 131 can receive messages on the chat with the terminal device 10 via the predetermined message application. For example, the reception unit 131 receives a message request in response to an operation from the owner in response to a message displayed on the chat.

The reception unit 131 also receives preference information related to the preferences of pet owners and pet information related to the pet. In the example of FIG. 1, the reception unit 131 receives answers to questions via chat. For example, the reception unit 131 receives answers to each question by selecting from options notified along with the question. The reception unit 131 also receives answers to each question entered by the owner in free format. The reception unit 131 then stores the received answers in the owner information storage unit 121 or the pet information storage unit 122.

(Regarding the determination unit 132)
The determination unit 132 determines various information. The determination unit 132 determines a pet food to recommend to the owner based on the preference information and pet information received by the reception unit 131. In the example of Fig. 1 , the determination unit 132 determines a pet food to recommend to the owner based on the answer. For example, the determination unit 132 inputs the preference information received in response to a question and the pet information, and determines a pet food to recommend to the owner using the learning model 123 that outputs a score indicating whether a specific pet food is optimal.

The learning model 123 has previously learned the relationship between a given owner's preference information, pet information, and the pet food selected by the owner, and when preference information and pet information are input, it outputs a score indicating the degree to which the given pet food is optimal.

To give a more specific example, if the preference information indicates that the owner is health-conscious and the pet information indicates that the pet weighs more than pets of the same age and breed, the determination unit 132 inputs this preference information and the pet information into the learning model 123. Then, if the pet food for which the score output by the learning model 123 is equal to or greater than a predetermined threshold is pet food "ABC," the determination unit 132 determines that pet food "ABC" is the pet food to recommend to the owner. Here, pet food "ABC" is a low-calorie pet food that can prevent weight gain when consumed by a pet.

Furthermore, if the preference information indicates that the owner is an owner who is interested in pet preferences and the pet information indicates that the pet's weight is a standard weight, the determination unit 132 inputs this preference information and this pet information into the learning model. Then, if the pet food for which the score output by the learning model is equal to or greater than a predetermined threshold is pet food "XYZ," the determination unit 132 determines that pet food "XYZ" is the pet food to recommend to the owner. Here, pet food "XYZ" is made using domestic beef as an ingredient, and has a good texture and a fragrant aroma that stimulates the pet's appetite.

(Regarding the providing unit 133)
The providing unit 133 notifies or provides various types of information. Specifically, the providing unit 133 notifies the terminal device 10 of a message on a chat via a predetermined message application. In the example of FIG. 1 , the providing unit 133 notifies the terminal device 10 of a question on the chat. For example, the providing unit 133 notifies the terminal device 10 of a question regarding the owner's preferences, a question regarding the pet, or the like.

To give a more specific example, the providing unit 133 may notify questions about the owner's preferences, such as whether the owner is concerned about the health of their pet, or what the owner pays attention to when feeding pet food to their pet.

In addition, the providing unit 133 notifies the owner of questions regarding their preferences, such as questions about what they pay attention to when selecting pet food, questions about whether they select pet food with the pet's health as their main focus or whether they select pet food with the pet's preferences as their main focus, and questions about whether they value interacting with their pet. In addition to questions regarding the owner's preferences, the providing unit 133 may also notify questions regarding the owner's age, gender, number of pets, family composition, etc.

The providing unit 133 also notifies the user of questions about pets, such as questions about pet attributes. For example, the information processing device 100 notifies the user of questions about the pet's type, age, sex, weight, body conditioning score, whether the pet has been neutered, preferences, etc.

The providing unit 133 also notifies the user of questions about the pet, such as questions about the food the pet has eaten. For example, the information processing device 100 notifies the user of questions about the date and time the food was eaten, or the mealtime if the pet eats twice a day, the food, the amount eaten, etc.

The providing unit 133 may also notify various types of information using push notifications. The providing unit 133 may also change the timing of push notifications depending on the owner information stored in the owner information storage unit 121.

The providing unit 133 also provides the owner with information about the pet food selected by the selecting unit 132 from among the pet foods stored in the product information storage unit 124. For example, the providing unit 133 provides the terminal device 10 with a message including advertising content related to pet food "ABC" and information for redirecting the user to an internet shopping site where pet food "ABC" can be purchased.

Furthermore, if the intake amount indicated by the intake status of pet food "ABC" is below a predetermined threshold, the providing unit 133 may provide the owner with information about similar pet foods that are different from pet food "ABC."

(Regarding the acquisition unit 134)
The acquisition unit 134 acquires various types of information. Specifically, the acquisition unit 134 may acquire the intake status of the pet food provided by the provision unit 133 after a predetermined period of time has passed. For example, assume that questions regarding the date and time when pet food "ABC" was consumed, the amount of pet food "ABC" eaten, etc. have been notified. In this case, the acquisition unit 134 acquires the intake status of pet food "ABC" by accepting answers to such questions.

(Regarding the update unit 135)
The update unit 135 updates the parameters of the learning model 123. For example, the update unit 135 updates the parameters of the learning model 123 based on the intake status of pet food "ABC." For example, the update unit 135 updates the parameters of the learning model 123 by learning the relationship between the preference information of the owner who purchased pet food "ABC" and information on the amount eaten, included in the intake status of pet food "ABC" by the pet.

For example, the update unit 135 performs a learning process for the learning model using a method such as backpropagation (backpropagation method). In this case, the update unit 135 adjusts the weight values that are taken into account when values are transmitted between nodes through the learning process. In this way, the update unit 135 learns through a process such as backpropagation, which corrects parameters so as to reduce the error between the output (first output and second output) in the learning model 123 and the correct answer (classification label) corresponding to the input. The update unit 135 also updates the parameters of the learning model by performing a process such as backpropagation so as to minimize a predetermined loss function.

[4. Processing Procedure (1)]
Next, a procedure of a provision process executed by the information processing apparatus 100 according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of the flow of the provision process executed by the information processing apparatus 100 according to the embodiment.

As shown in FIG. 6, the reception unit 131 receives a chat (step S101). Specifically, the reception unit 131 receives a chat (message) from a terminal device 10 on which a predetermined message application is installed. For example, if the reception unit 131 has not received a chat (step S101; No), the reception unit 131 waits until a chat is received.

On the other hand, if the reception unit 131 receives a chat (Step S101; Yes), it receives preference information and pet information (Step S102).

Then, the determination unit 132 uses the learning model 123 to determine the pet food to recommend to the owner based on the preference information and pet information received by the reception unit 131 (step S103).

Then, the providing unit 133 provides information about the pet food determined by the determining unit 132 (step S104).

[5. Processing Procedure (2)]
Next, the procedure of the update process executed by the information processing apparatus 100 according to the embodiment will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of the flow of the update process executed by the information processing apparatus 100 according to the embodiment.

As shown in FIG. 7, the acquisition unit 134 determines whether it is a predetermined timing (step S201). Specifically, if the acquisition unit 134 determines that it is not a predetermined timing (step S201; No), it waits until the predetermined timing arrives.

On the other hand, if the acquisition unit 134 determines that the predetermined timing has arrived (Step S201; Yes), it acquires intake information (Step S202). Then, the update unit 135 updates the learning model 123 based on the intake information (Step S203).

6. Modifications
The information processing device 100 described above may be implemented in various different forms other than the above embodiment, so other embodiments of the information processing device 100 will be described below.

[6-1. Orientation information]
Furthermore, the preference information may include information regarding the owner's requests, such as suppressing the odor of pet excrement, or the raw materials, nutrients, or toppings that the owner wants their pet to consume.

[6-2. Pet Information]
Furthermore, the pet information may include information about the pet from the owner's perspective. For example, the pet information may include information about the pet's allergies, allergenic ingredients, or ingredients to avoid. The pet information may also include information about the pet's activity level, including the pet's activity level, and information about the pet's medical history or symptoms of concern. Here, examples of symptoms of concern include, for example, if the pet is a cat, the rate at which the pet vomits hairballs, regurgitation of hairballs, lower urinary tract stones, or inability to eat hard cat food.

The pet information may also include information obtained based on sensor information attached to the pet. For example, the pet information may include information about the amount of exercise the pet does obtained by an acceleration sensor or gyro sensor, or information about the amount of excrement obtained by a sensor that detects the amount of excrement installed in the toilet used by the pet.

Pet information may also include information that changes over time, such as changes in the pet's weight, changes in the amount of pet food consumed, and changes in the amount of excrement excreted. Pet information may also include information about the pet's common behaviors and information about the pet's genes.

[6-3. Learning model]
In the above embodiment, an example was given in which the learning model pre-learns the relationship between a given owner's preference information, pet information, and the pet food selected by the owner, and when preference information and pet information are input, the learning model outputs a score indicating the degree to which a given pet food is optimal or not. However, this is not limited to this, and the learning model may be any type of learning model.

For example, the learning model may have previously learned the relationship between a given owner's preference information, pet information, and side dishes selected by the owner. In this case, the learning model may be a learning model that outputs a score indicating whether or not a given side dish is optimal when the preference information and pet information are input. The learning model may also be a learning model that has previously learned the relationship between a given owner's preference information, pet information, and combinations of main dishes and side dishes selected by the owner. In this case, the learning model may be a learning model that outputs a score indicating whether or not a given combination of main dishes and side dishes is optimal when the preference information and pet information are input.

The learning model is also assumed to have previously learned the relationship between a specific owner's preference information, pet information, and pet food containing the ingredients selected by the owner. In this case, the learning model may be a model that, when preference information and pet information are input, outputs a score indicating the degree to which a specific pet food containing the ingredients selected by the owner is optimal.

The learning model is also assumed to have previously learned the relationship between a given owner's preference information, the number of pets included in the owner information, the pet information, and the pet food selected by the owner. In this case, the learning model may be a learning model that outputs a score indicating the degree to which a given pet food is optimal when the preference information, the number of pets, and the pet information are input. By using such a learning model, the determination unit 132 can thereby determine the optimal pet food for the majority of pets to consume. Furthermore, if a learning model is generated that places a high weight on pet preferences, the determination unit 132 can determine pet food that matches the preferences of each pet.

The learning model may be a model that learns various pieces of information after setting the weight of specific information to 0 based on rules set by the administrator who manages the information processing device 100. For example, suppose the answer received from the owner includes information about ingredients that cause allergies. In this case, the administrator may set the weight associated with pet food that contains such allergenic ingredients to 0.

[6-4. Pet food]
In the above embodiment, the description has been given using pet food as an example, but the present invention is not limited thereto. For example, the providing unit 133 may provide information on side dishes such as snacks. In this case, the determining unit 132 may determine a side dish to be proposed to the owner using a learning model that has previously learned the relationship between a predetermined owner's preference information, pet information, and the side dish selected by the owner, and that outputs a score indicating whether the predetermined side dish is optimal when the preference information and pet information are input.

The providing unit 133 may also provide information regarding combinations of staple foods and side dishes, such as combinations of pet food and snacks. In this case, the determining unit 132 may determine a combination of staple foods and side dishes to be suggested to the owner using a learning model that has previously learned the relationship between a given owner's preference information, pet information, and the combination of staple foods and side dishes selected by the owner, and that outputs a score indicating the degree to which the combination of a given staple food and side dish is optimal when the preference information and pet information are input.

[6-5. Information related to pet food]
In the above embodiment, an example of a provision process in which the provision unit 133 provides the owner with information about the pet food determined by the determination unit 132 has been described, but the present invention is not limited to this. For example, the provision unit 133 may provide the owner with related information that is related to the information about the pet food. In this case, the provision unit 133 may provide the owner with at least one of the following related information: information about the ingredients of the pet food, information about the nutritional components contained in the pet food, information about additives added to the pet food, information about the place of origin of the ingredients of the pet food, and information about the place of production where the pet food was produced.

The providing unit 133 may also provide the owner with related information that explains to the owner what effects the nutritional components of the pet food have, what effects it has on the pet, etc. The providing unit 133 may also provide to the owner with related information that clearly explains the appealing features of the pet food, such as being fragrant, juicy, crunchy, etc.

[6-6. Feeding Information]
In the above embodiment, an example of a determination process in which the determination unit 132 determines a pet food to recommend to the owner based on preference information and pet information has been described, but the present invention is not limited to this. For example, the determination unit 132 may determine a pet food to recommend to the owner based on feeding information, preference information, and pet information. Here, feeding information refers to information related to a method of feeding a pet.

For example, feeding information includes information on whether pets are fed in small portions, in packaged form such as cans or pouches, whether pet food is distributed to pets in designated containers, or whether the owner feeds the pet directly.

For example, the determination unit 132 determines the pet food to recommend to the owner using a learning model that inputs feeding information, preference information, and pet information and outputs a score indicating the degree to which a specific pet food is optimal.

Here, the learning model pre-learns the relationship between a given owner's preference information, pet information, feeding information, and the pet food selected by the owner, and when feeding information, preference information, and pet information are input, it outputs a score indicating the degree to which the given pet food is optimal.

To give a more specific example, the determination unit 132 assumes that the owner's preference indicated by the preference information is a preference for valuing contact with pets, and that the owner feeds pet food directly to the pet. In this case, the determination unit 132 inputs the feeding information, preference information, and pet information into the learning model. Then, if the pet food for which the score output by the learning model is equal to or greater than a predetermined threshold is the pet food "KLM," the determination unit 132 may determine that the pet food to be recommended to the owner is the pet food "KLM." Here, the pet food "KLM" is pet food that is portioned into predetermined containers to make it easy to feed directly to the pet.

As a result, the decision unit 132 of the information processing device 100 according to the embodiment decides on the pet food to recommend to the owner based on the feeding information, preference information, and pet information, and is therefore able to determine information on appropriate pet food that reflects the owner's preferences.

[6-7. External environment information〕
In the above embodiment, an example of a determination process in which the determination unit 132 determines a pet food to recommend to the owner based on preference information and pet information has been described, but the present invention is not limited to this. For example, the determination unit 132 may determine a pet food to recommend to the owner based on external environment information, preference information, and pet information.

For example, the determination unit 132 inputs external environmental information, including information about the weather, temperature or room temperature, and humidity, as well as preference information and pet information, and uses a learning model to determine the pet food to recommend to the owner, outputting a score indicating the degree to which a specific pet food is optimal.

The learning model pre-learns the relationship between a given owner's preference information, pet information, external environment information, and the pet food selected by the owner, and when external environment information, preference information, and pet information are input, it outputs a score indicating the degree to which the given pet food is optimal.

To give a more specific example, the determination unit 132 assumes that the preference information indicates that the owner is health-conscious, the pet information indicates that the pet weighs more than pets of the same age and breed, and it is the rainy season. In this case, the determination unit 132 inputs the external environment information, preference information, and pet information into the learning model. Then, if the pet food for which the score output by the learning model is equal to or greater than a predetermined threshold is pet food "KLM," the determination unit 132 determines that pet food "KLM" is the pet food to recommend to the owner. Here, pet food "KLM" is a low-calorie pet food because it is predicted that walking with pets will not be possible during the rainy season, and consuming pet food "KLM" is a pet food that can prevent weight gain for pets.

As a result, the decision unit 132 of the information processing device 100 according to the embodiment decides on the pet food to recommend to the owner based on the external environment information, preference information, and pet information, and is therefore able to determine information on appropriate pet food that reflects the owner's preferences.

[6-8. Information from veterinarians]
In the above embodiment, an example of a process for determining a pet food to be recommended to the owner by the determination unit 132 based on the preference information and the pet information has been described, but the process is not limited to this. For example, the determination unit 132 may determine a pet food to be recommended to the owner by using information provided by a veterinarian as information provided from outside.

For example, the determination unit 132 inputs information provided by a veterinarian, preference information, and pet information, and uses a learning model to output a score indicating the degree to which a specific pet food is optimal to determine the pet food to recommend to the owner.

The learning model pre-learns the relationship between a given owner's preference information, pet information, information provided by a veterinarian, and the pet food selected by the owner, and when the information provided by the veterinarian, preference information, and pet information are input, it outputs a score indicating the degree to which the given pet food is optimal.

To give a more specific example, the determination unit 132 assumes that the preference information indicates that the owner is health-conscious, the pet information indicates that the pet weighs more than other pets of the same age and breed, and the information provided by the veterinarian indicates that the pet is slightly obese. In this case, the determination unit 132 inputs the information provided by the veterinarian, the preference information, and the pet information into the learning model. Then, if the pet food for which the score output by the learning model is equal to or greater than a predetermined threshold is pet food "KLM," the determination unit 132 determines that pet food "KLM" is the pet food to recommend to the owner. Here, pet food "KLM" is a low-calorie pet food that can prevent weight gain when consumed by a pet.

As a result, the decision unit 132 of the information processing device 100 according to the embodiment determines the pet food to recommend to the owner based on the information provided by the veterinarian, the preference information, and the pet information, and is therefore able to determine information regarding appropriate pet food that reflects the owner's preferences.

Furthermore, when considering the health of pets, knowing what nutrients a pet food a pet eats each day and in what amounts can make it easier for veterinarians examining the pet to determine what is lacking or excessive in terms of health. For this reason, the information processing device 100 provides pet information to veterinarians, making it easier for the veterinarian to make various health-related suggestions to pet owners. In this way, the information processing device 100 can determine overeating and nutritional deficiencies based on the pet's type and ideal weight, and can provide advice on the optimal food and feeding method for a long and healthy life.

Furthermore, the decision unit 132 may decide on the pet food to recommend to the owner by prioritizing preference information, pet information, or information provided by a veterinarian.

[6-9. Estimating pet preferences]
Furthermore, the reception unit 131 may estimate the pet's preferences and health condition based on the received owner information and pet information. For example, the reception unit 131 may estimate the pet's preferences and health condition based on responses from the owner and various sensors (Internet of Things: IoT devices) attached to the pet.

[6-10. Other]
Of the above processes, all or part of the processes described as being performed automatically may be performed manually. Furthermore, all or part of the processes described as being performed manually may be performed automatically using known methods. Furthermore, the information, including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings, may be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown.

Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown. Furthermore, each component may be functionally or physically distributed and integrated in any unit, in whole or in part, depending on various loads, usage conditions, etc.

Furthermore, the processes described above may be combined as appropriate to the extent that they are not inconsistent.

Furthermore, the "parts" (sections, modules, units) mentioned above can be read as "means" or "circuits." For example, the reception unit can be read as reception means or reception circuit.

7. Hardware Configuration
The terminal device 10 and the information processing device 100 according to the above-described embodiments are realized, for example, by a computer 1000 configured as shown in Fig. 8. Fig. 8 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and is connected to a calculation device 1030, a cache 1040, a memory 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 via a bus 1090.

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

The output IF 1060 is an interface for transmitting information to be output to an output device 1010, such as a monitor or printer, which outputs various types of information, and may be implemented, for example, by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface). On the other hand, the input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, scanner, etc., and may be implemented, for example, by USB.

For example, the input device 1020 may be implemented as a device that reads information from optical recording media such as a CD (Compact Disc), DVD (Digital Versatile Disc), or PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be implemented as an external storage medium such as a USB memory.

Network IF 1080 has the function of receiving data from other devices via network N and sending it to the arithmetic device 1030, and also transmitting data generated by the arithmetic device 1030 to other devices via network N.

Here, 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 memory 1050 onto the cache 1040 and executes the loaded program. For example, when the computer 1000 functions as the information processing device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 by executing the program loaded onto the cache 1040.

The above describes in detail the embodiments of the present application based on the drawings. However, these are merely examples, and the embodiments of the present application can be implemented in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the Disclosure of the Invention section.

N Network 1 Information processing system 10 Terminal device 100 Information processing device 110 Communication unit 120 Storage unit 121 Owner information storage unit 122 Pet information storage unit 123 Learning model 124 Product information storage unit 130 Control unit 131 Reception unit 132 Decision unit 133 Provision unit 134 Acquisition unit 135 Update unit

Claims (11)

a receiving unit that receives preference information relating to the preference of a pet owner, the preference information indicating the tendency of the owner to keep the pet , and pet information relating to the pet;
a determination unit that determines a pet food to be recommended to the owner based on the preference information and the pet information;
a providing unit that provides the owner with information indicating the pet food determined by the determining unit. The determination unit
The information processing device according to claim 1, wherein the pet food is determined using a learning model that outputs a score indicating whether a predetermined pet food is optimal or not by inputting the preference information and the pet information. The reception unit
As the preference information, preference information regarding the health of the pet is received;
The determination unit
The information processing device according to claim 1 or 2, further comprising: determining a pet food to be recommended to the pet owner based on the pet information and the pet preference information regarding the pet's health. The reception unit
As the preference information, preference information regarding the pet's preferences is received;
The determination unit
4. The information processing device according to claim 1, further comprising: determining a pet food to be recommended to the owner based on preference information indicating the pet's preferences and the pet information. The reception unit
further receiving owner information that is information about the owner and is different from the preference information;
The determination unit
5. The information processing device according to claim 1, wherein the pet food to be recommended to the owner is determined based on the owner information, the preference information, and the pet information. The reception unit
receiving, as the owner information, feeding information regarding a feeding method for the pet;
The determination unit
The information processing device according to claim 5 , further comprising: determining a pet food to be recommended to the owner based on the feeding information, the preference information, and the pet information. The reception unit
Further receiving, as the owner information, external environment information relating to the environment around the place where the owner lives or the activity range in which the owner is active;
The determination unit
The information processing device according to claim 5 or 6, wherein the pet food to be recommended to the owner is determined based on the external environment information, the preference information, and the pet information. The providing unit
8. The information processing device according to claim 1, further comprising: providing the pet owner with information related to the pet food together with the information indicating the pet food. The providing unit
The information processing device according to claim 8, characterized in that the related information provided to the pet owner includes at least one of information regarding the ingredients of the pet food, information regarding the nutritional components contained in the pet food, information regarding additives added to the pet food, information regarding the country of origin of the ingredients of the pet food, and information regarding the country of manufacture where the pet food was produced. 1. A computer-implemented information processing method, comprising:
a receiving step of receiving preference information relating to the preference of a pet owner, the preference information indicating a tendency of keeping the pet , and pet information relating to the pet;
a determination step of determining a pet food to be recommended to the owner based on the preference information and the pet information;
a providing step of providing the owner with information indicating the pet food determined in the determining step. a receiving step for receiving preference information relating to the preference of a pet owner, the preference information indicating the tendency of the owner to keep the pet , and pet information relating to the pet;
a determination step of determining a pet food to be recommended to the owner based on the preference information and the pet information;
a provision step of providing information indicating the pet food determined by the determination step to the owner.