Information processing device and information processing method

Abstract

To easily and accurately predict user behavior in response to provided content.SOLUTION: An information processing device (10) comprises: an acquisition unit (11) which acquires provided content received from a real-world user and attribute information representing the nature of the provided content among provided content including at least one of products and services that can be offered to the real-world user; a profile generation unit (12) which generates a profile of a virtual user on the basis of the provided content offered to the real-world user and the attribute information corresponding to the provided content; and a behavior prediction unit (13) which predicts behavior of the real-world user on the basis of behavior of the virtual user having the profile generated by the profile generation unit with respect to provided content of a target in a virtual space.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device and an information processing method. [Background technology]

[0002] Patent Document 1 listed below describes a technology that collects social media posts related to a user, extracts their features, and estimates the frequency of visits to facility categories related to the social media posts. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-77821 Summary of the Invention [Problem to be solved by the invention]

[0004] Here, even if it is possible to estimate the visit frequency of a real user from the results of providing content to the real user as in the technology described in Patent Document 1, it is not possible to simulate what actions the user will take in response to the content. For this reason, when deciding whether to provide content, the decision is generally made by a real person, and the decision on whether to provide the content is generally made based on the experience of that person.

[0005] However, such judgments require highly advanced skills and experience, and therefore there is a need for a method to easily and appropriately predict user behavior regarding provided content.

[0006] Therefore, an object of the present disclosure is to easily and appropriately predict user behavior regarding provided content. [Means for solving the problem]

[0007] The information processing device according to the present disclosure includes an acquisition unit that acquires content provided to a real-world user from content provided that includes at least one of goods and services that can be provided to a real-world user, and property information that represents the properties of the content provided; a profile generation unit that generates a profile of a virtual user based on the content provided to the real-world user and the property information corresponding to the content provided; and a behavior prediction unit that predicts the behavior of a real-world user based on the behavior of a virtual user having a profile generated by the profile generation unit toward a target content provided in a virtual space. [Effects of the Invention]

[0008] According to the present disclosure, it is possible to easily and appropriately predict user behavior regarding provided content. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 2 is a functional block diagram of an information processing device and peripheral devices. [Figure 2] 10 is a diagram for explaining a process of predicting the behavior of a virtual user in response to target provided content in a virtual space. FIG. [Figure 3] FIG. 2 is a flowchart showing a process executed by the information processing device. [Figure 4] FIG. 2 is a diagram illustrating an example of a hardware configuration of an information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of an information processing device and an information processing method according to the present disclosure will be described with reference to the drawings.

[0011] FIG. 1 shows the configuration of an information processing system 1 including an information processing device 10 and its related devices. As shown in FIG. 1, the information processing system 1 includes the information processing device 10, a provided content database 3, a property information database 5, and a virtual space control server 30. The information processing device 10 predicts the behavior of a real-world user regarding the target provided content based on information obtained from the provided content database 3, the property information database 5, the virtual space control server 30, etc. Hereinafter, a real-world user may be referred to as a "real user."

[0012] The offerings include at least one of goods and services that can be provided to real users. A product is an item that has a physical form. A service is a right related to an experience or activity that does not have a physical form (for example, the right to participate in a specific event). The offerings may be paid or free of charge. The offerings may be virtual goods that can be used in the virtual space or services that the user enjoys in the virtual space, or real goods that are delivered to the user in the real world or services that the user enjoys in the real world. The offerings in this embodiment refer to paid goods that are sold at convenience stores and include food, drinks, miscellaneous goods, etc.

[0013] The behavior of real users regarding the offered content refers to visually checking (paying attention to) the location where the offered content is provided, and considering or deciding whether or not to receive the offered content (purchase it or not). The location where the offered content is provided includes the location where the offered content is placed, the location where the offered content can be received, etc. The location where the offered content is placed includes the facility where the offered content is provided, such as a store or facility, a shelf or corner within the facility, or a website.

[0014] A real user receives the provided content by, for example, applying for the provision of the provided content. Receiving the provided content includes acquiring or experiencing the provided content through purchasing the provided content. In this embodiment, receiving the provided content by a real user refers to the real user paying money for a product at a convenience store and acquiring the product.

[0015] The information processing device 10 is used to estimate the behavior of a virtual user in response to target content provided in a virtual space provided by the virtual space control server 30. Examples of the information processing device 10 include a desktop PC, a laptop PC, a smartphone, a tablet terminal, and a wearable terminal (e.g., a head-mounted display, smart glasses, etc.).

[0016] The information processing device 10 includes an acquisition unit 11 that acquires content provided to a real user from content that can be provided to a real user and property information that indicates the property of the content, a profile generation unit 12 that generates a profile of a virtual user based on the content provided to the real user and the property information corresponding to the content, a behavior prediction unit 13 that predicts the behavior of the real user based on the behavior of the virtual user with the profile in response to the target content in the virtual space, and an output unit 14 that outputs the behavior results of the real user. The output unit 14 includes, for example, at least one of a display and a storage device.

[0017] The acquisition unit 11 acquires the offer content provided to the real user from the offer content database 3. The offer content database 3 stores the offer content provided to the real user for each provision location (e.g., a store or facility). The offer content includes, for example, the name, type, and quantity of the offer content provided to the real user. The offer content may include at least one of information input by a provider (store clerk) who provides the offer content and information input by the real user (customer) when receiving the offer content. The offer content database 3 stores, for example, offer content acquired by a POS (Point of Sale) system (point of sale information management system).

[0018] Furthermore, the acquisition unit 11 acquires, from the property information database 5, property information corresponding to the content provided to the real user, which is acquired from the content database 3. The property information database 5 stores property information.

[0019] The property information includes at least one of detailed information about the offer, information about the target of the offer, and information about the environment in which the offer is provided. The detailed information includes the name of the offer, the quantity included in each offer, the nutritional content of the offer, the contents described on the package, the concept of the offer, etc.

[0020] The target of the content to be provided is a user to whom the provider who is planning to provide the content to be provided intends to provide the content to. Information about the target of the content to be provided includes gender, age, affiliated organization, lifestyle, whether the target is accompanied or not, etc. Information about the environment in which the content to be provided includes the date, time period, weather, location (an example of the location where the content to be provided) when the content to be provided is provided, the congestion status of the location, and the manner in which the content to be provided is provided.

[0021] For example, a case will be described in which the content provided to a real user is a single energy drink. The property information of the energy drink includes, for example, detailed information about the package and information about the concept. The information about the package, for example, lists several types of vitamin ingredients and includes content encouraging nutritional supplementation. The information about the concept includes, for example, content aiming to recover from fatigue. The property information of the energy drink includes, for example, information about the target of the content, content that the target is an adult male who works in an office and has poor daytime concentration. The property information of the energy drink includes, for example, information about the environment in which the content is provided, content that the day is Wednesday morning, the humidity is 70%, the weather is sunny, the energy drink is sold in a relatively empty convenience store, and the energy drink is displayed with a pop-up by the store clerk.

[0022] Furthermore, the acquisition unit 11 acquires the target content to be provided for predicting the behavior of real users from the content to be provided database 3. The content to be provided further includes, for example, information about the target content to be provided that is being considered for provision by the content to be provided provider. The information about the target content to be provided includes the name, type, and quantity of the target content to be provided. The content to be provided database 3 stores, for example, the content to be provided output from a terminal owned by the content to be provided provider via a communication network (not shown).

[0023] The target offering may be an offering that can be provided to a user in the real world, and includes an offering that is different from an existing offering that is planned to be provided to a user in the real world in the future. The target offering in this embodiment is different from the offering that a user in the real world has received. The target offering includes an offering in the prototype stage, an offering before release, etc.

[0024] The profile generation unit 12 generates a profile of a virtual user based on the content provided by the real user and the attribute information corresponding to the content. Specifically, the profile generation unit 12 has a built-in Large Language Model (LLM) that has previously learned a vast amount of linguistic information and includes attribute information of real users. The attribute information includes at least one of the virtual user's gender, age, family structure, organization affiliation, lifestyle, personality, and preferences. The profile generation unit 12 inputs a query statement including the content provided and the attribute information into the LLM to obtain a profile of the virtual user output from the LLM. The type and quantity of the content provided input in the query statement may vary depending on the real user. Note that it is not essential for the profile generation unit 12 to incorporate an LLM; the profile generation unit 12 may obtain the above-mentioned virtual user profile by, for example, querying an LLM in an external device (such as a cloud server).

[0025] An example of a virtual user profile generated by the profile generation unit 12 will be described using the example of a real user who received the above-mentioned energy drink. The profile generation unit 12 inputs the energy drink as the content to be provided into the query. The profile generation unit 12 inputs the above-mentioned detailed information, information about the target of the content to be provided, and information about the environment in which the content to be provided into the query as characteristic information. The profile generation unit 12 inputs the query into the LLM to obtain a virtual user profile output from the LLM. The profile includes information such as that the virtual user is a single adult male, a busy office worker with daily work, prone to jumping on trends, and eager to work energetically. In this way, the virtual user profile includes at least one attribute information of the virtual user's gender, age, family structure, organization, lifestyle, personality, and preferences.

[0026] The profile generation unit 12 generates a profile for at least one virtual user. The profile generation unit 12 generates, for example, profiles for a plurality of virtual users. In this case, for example, the profile generation unit 12 generates profiles for a plurality of different virtual users based on the content provided to the plurality of real users and the attribute information corresponding to the content provided. The content provided to the plurality of real users may differ in type, number, etc. for each real user. For this reason, the virtual user profile is generated based on the content provided that differs for each real user and the attribute information corresponding to the content provided, and therefore the profiles of the plurality of virtual users may differ from one another. The profiles of different virtual users include those in which at least a portion of the attribute information included in the profiles is different.

[0027] The profile generation unit 12 may generate profiles of multiple virtual users and further generate profiles of virtual users having attribute information indicating the characteristics of the multiple virtual users based on the profiles of the multiple virtual users. The profile generation unit 12 estimates the attribute information that is characteristic of the multiple virtual users by performing clustering or topic analysis on the profiles of the multiple virtual users.

[0028] The profile generation unit 12 estimates attribute information characteristic of a plurality of virtual users by, for example, clustering the profiles of the plurality of virtual users. In this case, the profile generation unit 12 classifies the profiles of the plurality of virtual users having similar features into the same cluster, and sets the features as attribute information. As a clustering technique, the k-means method, Latent Dirichlet Allocation (LDA), or the like is used.

[0029] The profile generation unit 12 estimates attribute information characteristic of a plurality of virtual users by, for example, performing topic analysis on the profiles of the plurality of virtual users. In this case, the profile generation unit 12 identifies each topic in the profiles of the plurality of virtual users and sets the common topic as attribute information.

[0030] The profile generation unit 12 generates a representative profile of virtual users who are likely to visit the offering location by generating a virtual user profile having attribute information indicating the characteristics of a plurality of virtual users. The profile generation unit 12 generates the representative profile of the virtual user based on at least one feature included in the attribute information estimated by clustering or topic analysis. For example, the profile generation unit 12 generates the representative profile of the virtual user based on pre-stored attribute information of real users and at least one feature included in the attribute information estimated by clustering or topic analysis. The representative profile of the virtual user includes at least one profile.

[0031] The profile generation unit 12 outputs the generated profile to the output unit 14. The output unit 14 stores the profile. The output unit 14 may display the profile.

[0032] The behavior prediction unit 13 estimates the behavior of a virtual user having a profile generated by the profile generation unit 12 with respect to the target offered content in the virtual space. The behavior prediction unit 13, for example, works in cooperation with a virtual space control server 30 that controls the entire metaverse space, and causes the output unit 14 to display the metaverse space as shown in Fig. 2. The behavior prediction unit 13 sets up a virtual facility (in one example, a virtual store 31) that provides the offered content in the metaverse space, and acquires information regarding the behavior of a virtual user having the above profile with respect to the target offered product.

[0033] The virtual user's behavior with respect to the target offering refers to at least one of the following actions: passing in front of the location where the target offering is provided, looking at the target offering, paying attention to the offering, considering whether or not to accept the offering (whether or not to purchase it), picking up the offering to check it if looking at it, returning the offering to its original position if picking it up, and deciding to accept (purchase) the offering if picking it up.

[0034] A virtual user receiving content includes a virtual user in a virtual space acquiring the content through a request for the provision of the content in the virtual space. In this embodiment, a virtual user receiving content refers to a virtual user paying money for a product in a virtual store and acquiring the product. Hereinafter, a virtual user in a virtual space may be referred to as an avatar.

[0035] The behavior prediction unit 13 sets conditions for providing the content to be provided in the virtual space before estimating the behavior of the avatar with respect to the target content to be provided. The behavior prediction unit 13 places the content to be provided in the virtual space under the set conditions for providing the content to be provided. The behavior prediction unit 13 extracts an index included in the property information of the content to be provided acquired by the acquisition unit 11 from the property information database 5, and generates at least one condition for providing the content to be provided.

[0036] The behavior prediction unit 13 predicts the behavior of the avatar by changing the conditions for providing the content in the virtual space in multiple ways. The conditions for providing the content in the virtual space (metaverse space) include at least one of the date, time period, weather, location, congestion level of the location, the mode of providing the content, and whether the avatar is accompanied. Changing the conditions for providing the content includes changing the environment of the metaverse space. The above-mentioned date includes the day of the week, the target sales period, etc. The above-mentioned time period includes morning, noon, evening, late night, etc. The above-mentioned location of the content includes the type of facility and store, the location in the store (corner location), the top, center, or bottom of the shelf in the corner, etc.

[0037] The behavior prediction unit 13 outputs the generated provision conditions to the output unit 14. The output unit 14 stores the provision conditions. Note that the behavior prediction unit 13 does not have to generate the provision conditions. In this case, the acquisition unit 11 may acquire preset provision conditions from a server within the information processing device 10 or from an external server of the information processing device 10.

[0038] An example of the behavior of an avatar in response to the target offering content, as estimated by the behavior prediction unit 13, will be described below with reference to FIG. 2. The behavior prediction unit 13, for example, cooperates with the virtual space control server 30 to cause an avatar 60 having the above profile in the metaverse space to enter a virtual store 31. The behavior prediction unit 13 estimates (simulates) the behavior of the avatar that has entered the virtual store 31 in response to the target offering content. The virtual store 31 is an example of a facility in the virtual space that is assumed to provide the target offering content in the metaverse space. The virtual store 31 is, for example, a convenience store.

[0039] The target content to be provided is acquired by the acquisition unit 11. The behavior prediction unit 13 is arranged in the virtual store 31 in accordance with the provision conditions generated (acquired) for the target content to be provided.

[0040] The avatar 60 that enters the virtual store 31 acts within the virtual store 31 based on the profile generated by the profile generation unit 12. The avatar 60 acts in relation to the target offerings within the virtual store 31 according to the attribute information included in the profile.

[0041] The behavior of avatar 60 generated based on a profile set based on the above-mentioned energy drink is illustrated below. The target offering is a new energy drink. The target offering is, for example, placed in beverage section A according to the offering conditions. For example, avatar 60 entering virtual store 31 behaves as if searching for a product that will help energize the user within virtual store 31 based on the profile. Because avatar 60 is busy, avatar 60 behaves as if searching for a drink that can be consumed easily, and moves past beverage sections A and B. Avatar 60 discovers a new energy drink in beverage section A, picks it up, and examines it. Wanting to jump on the trend, avatar 60 immediately decides to purchase the new energy drink and pays for it. In this case, behavior prediction unit 13 acquires information regarding the behavior of the avatar entering virtual store 31 regarding the target offering, including the behavior of viewing the offering, the behavior of picking up the offering, the fact that there was no consideration time before purchasing, and the behavior of purchasing the offering (receiving the offering).

[0042] The target offering is not limited to the same type of offering as the offering referenced when the profile of the avatar 60 was generated, and may be another type of offering. For example, the target offering may be a new sandwich. The avatar 60 enters the store during lunchtime and, being busy, acts to look for food that can be easily consumed, so moves past food sections A to J. The avatar 60 discovers a new sandwich in food section B, picks it up, and examines it. The avatar wants to join the trend, but thinks there is a more energizing product, so decides not to purchase the new sandwich and returns the sandwich to food section B. In this case, the behavior prediction unit 13 acquires, as information regarding the behavior of the avatar 60 entering the virtual store 31 with respect to the target offering, the behavior of viewing the offering, the behavior of picking up the offering, the fact that the consideration time before purchase is a predetermined time, and the behavior of not purchasing the offering (not receiving the offering).

[0043] In this way, the behavior prediction unit 13 predicts the behavior of the avatar 60 having the profile generated by the profile generation unit 12 in response to the target provided content in the virtual space.

[0044] Furthermore, the behavior prediction unit 13 predicts the behavior of a real user based on information about the behavior of the avatar 60 with respect to the estimated target offered product. The behavior prediction unit 13 may, for example, predict that the behavior of the avatar 60 under a plurality of mutually different provision conditions indicates the behavior of a real user. The behavior prediction unit 13 may, for example, predict that the behavior of a plurality of avatars 60 in the virtual store 31 indicates the behavior of a real user in a physical store. The behavior prediction unit 13 may, for example, predict that the behavior of an avatar 60 having a profile including attribute information that is identical to or similar to at least a part of a profile of a target of the offered content set by a provider of the offered content indicates the behavior of a real user. The behavior prediction unit 13 may predict that the behavior of a real user who has the same or similar profile as the profile set for the avatar 60 matches the behavior of the avatar 60.

[0045] An information processing method executed by the information processing device 10 will be described below with reference to the flowchart shown in Fig. 3. As a premise, at the start of the information processing method, the provided content received by the real user has already been stored in the provided content database 3, and the property information corresponding to the provided content has already been stored in the property information database 5. Also, as a premise, at the start of the information processing method, the target provided content, which is the target of predicting the behavior of the real user, has already been acquired by the information processing device 10.

[0046] First, in step S1, the acquisition unit 11 acquires from the provision content database 3 the provision content that the real user has received from among the provision content that can be provided to the real user, and acquires from the property information database 5 the property information corresponding to the provision content.

[0047] Next, in step S2, the profile generation unit 12 generates a profile of the avatar 60 based on the content provided by the real user and the property information corresponding to the content provided. The profile generation unit 12 may output the generated profile to the output unit 14. The output unit 14 may store the generated profile.

[0048] Next, in step S3, the behavior prediction unit 13 places an avatar 60 having the generated profile in the virtual space. The behavior prediction unit 13 cooperates with the virtual space control server 30, which controls the entire metaverse space, to cause the output unit 14 to display a virtual store 31 as part of the metaverse space, as shown in Fig. 2. The behavior prediction unit 13 cooperates with the virtual space control server 30 to control the output unit 14 to display the avatar 60 in the virtual store 31.

[0049] Next, in Step S4, the behavior prediction unit 13 sets a provision condition for the target content to be provided in the virtual space. Specifically, the behavior prediction unit 13, in cooperation with the virtual space control server 30, sets the provision condition based on the content to be provided that is planned to be provided in the virtual store 31 and property information corresponding to the content to be provided. The behavior prediction unit 13 may set one of the generated plurality of provision conditions. In the example shown in FIG. 2, when the content to be provided is a beverage, the behavior prediction unit 13 may generate a provision condition for arranging the content to be provided in beverage corner A and a provision condition for arranging the content to be provided in beverage corner B. The behavior prediction unit 13 may output the generated provision conditions to the output unit 14. The output unit 14 may store the generated provision conditions. In Step S4, the behavior prediction unit 13 sets the provision condition for the target content to a provision condition for arranging the content to be provided in beverage corner A.

[0050] Next, in step S5, the behavior prediction unit 13 assigns the target offering content to the virtual space. Specifically, the behavior prediction unit 13 cooperates with the virtual space control server 30 to arrange the offering content in the virtual store 31 based on the offering conditions. In this embodiment, the behavior prediction unit 13 arranges the offering content in the beverage corner A.

[0051] Next, in step S6, the behavior prediction unit 13 estimates (simulates) the behavior of the avatar 60. Specifically, the behavior prediction unit 13 works in cooperation with the virtual space control server 30 to make the avatar 60 act in the virtual store 31 and estimates the behavior in relation to the provided content. The avatar 60 acts in relation to the target provided content in the virtual store 31 according to the attribute information included in the profile. The behavior prediction unit 13 outputs information related to the behavior of the avatar 60 in relation to the target provided content to the output unit 14. The output unit 14 stores information related to the behavior of the avatar 60 in relation to the target provided content.

[0052] Next, in step S7, the behavior prediction unit 13 predicts the behavior of the real user with respect to the target provided content. As a specific example in the flowchart shown in FIG. 3, the behavior prediction unit 13 predicts that the behavior of a real user who is the same as or similar to the profile set in the avatar 60 will match the behavior of the avatar 60. The behavior prediction unit 13 outputs information related to the predicted behavior of the real user with respect to the target provided content to the output unit 14. The output unit 14 stores information related to the behavior of the real user with respect to the target provided content.

[0053] Next, in step S8, the behavior prediction unit 13 determines whether or not the behavior of the avatar 60 with respect to the target provision content has been estimated for all patterns of the set provision conditions. If the behavior prediction unit 13 determines in step S8 that the behavior of the avatar 60 with respect to the target provision content has not been estimated for all patterns of the provision conditions (NO in step S8), the behavior prediction unit 13 proceeds to step S9.

[0054] The behavior prediction unit 13 switches the serving conditions to another pattern in step S9. The behavior prediction unit 13 sets serving conditions different from the serving conditions that have already been set in step S4 (or step S9). As an example of the present embodiment, the behavior prediction unit 13 switches the serving conditions for the target serving content to serving conditions for placing the serving content in beverage corner B in step S9, and returns to step S5.

[0055] If the behavior prediction unit 13 determines in step S8 that the behavior of the avatar 60 in response to the target provision content has been estimated for all patterns of provision conditions (YES in step S8), the information processing method ends. When estimating the behavior of an avatar 60 with a different profile in response to the provision content, the information processing method may be started again from step S1 or step S2.

[0056] In the embodiment described above, the profile generation unit 12 of the information processing device 10 generates a profile of a virtual user (avatar 60) based on the content provided to the real user and the attribute information corresponding to the content. Therefore, it is not necessary to conduct a survey of real users who have received the content in the real world, and the profile of the virtual user is acquired. Furthermore, the behavior prediction unit 13 predicts the behavior of the real user based on the behavior of the virtual user with the profile generated by the profile generation unit 12 in response to the target content in the virtual space. Therefore, the behavior of the virtual user in response to the target content in the virtual space is estimated based on the behavior of the virtual user. Therefore, the behavior prediction unit 13 can easily predict the behavior of the real user based on the behavior of the virtual user with the generated profile. Therefore, the information processing device 10 and the information provision method make it possible to easily and appropriately predict the behavior of a user in response to the content provided.

[0057] The profile generation unit 12 also generates profiles for multiple virtual users and, based on the profiles of the multiple virtual users, further generates profiles for virtual users having attribute information indicating the characteristics of the multiple virtual users. In this case, the profile generation unit 12 generates virtual users having attribute information indicating characteristics common to real users to whom the content is provided, so it is possible to generate a predetermined number of virtual users greater than the number of real users. The profile generation unit 12 may also generate virtual users with profiles different from those of real users. This allows the behavior prediction unit 13 to estimate the behavior of more virtual users than real users with respect to the target content. Therefore, the behavior prediction unit 13 can more appropriately predict the behavior of real users with respect to the target content based on the results of the behavior of many virtual users.

[0058] Furthermore, the profile generation unit 12 estimates attribute information characteristic of the multiple virtual users by performing clustering or topic analysis on the profiles of the multiple virtual users. In this case, attribute information can be easily extracted from the profiles of the multiple virtual users.

[0059] The behavior prediction unit 13 also changes the conditions for providing the content in the virtual space in multiple ways and predicts the behavior of the real user based on the behavior of the virtual user. The conditions for providing the content include at least one of the date, time period, weather, location, congestion level of the location, the mode of providing the content, and whether the virtual user is accompanied by someone. This makes it possible to estimate the behavior of a virtual user with a profile generated based on the content and property information under various conditions (environments) in the virtual space for various types of content. This makes it easy to predict how a real user will behave in response to various types of content. The behavior prediction unit 13 can also predict the behavior of a real user based on the estimated results of the virtual user's behavior, without incurring the cost of conducting a survey each time.

[0060] The property information includes at least one of detailed information about the content to be provided, information about the target of the content to be provided, and information about the environment in which the content to be provided is provided. The profile generation unit 12 generates a profile based on the property information and the content to be provided acquired by the acquisition unit 11. Therefore, by having a wealth of information indicating the property of the content to be provided, it is possible to generate a profile that is more suited to the content to be provided.

[0061] Furthermore, the target content of provision is different from the content provided to the real user. In this case, the behavior prediction unit 13 can estimate the behavior in the virtual space of a virtual user who has a profile generated based on the content and property information different from the content of provision provided to the real user, even for content provided in the prototype stage or content provided before release. Therefore, the behavior prediction unit 13 can easily predict how a real user will behave with respect to content provided in the prototype stage, content provided before release, or other content different from the content provided to the real user.

[0062] The gist of the present disclosure lies in the following [1] to [7]. [1] An acquisition unit that acquires content provided to a user in the real world, including at least one of a product and a service that can be provided to the user in the real world, and property information that represents the property of the content provided; a profile generation unit that generates a profile of a virtual user based on the provided content received by the user in the real world and the property information corresponding to the provided content; a behavior prediction unit that predicts the behavior of the user in the real world based on the behavior of the virtual user having the profile generated by the profile generation unit with respect to the provided content of the target in the virtual space; An information processing device comprising: [2] The profile generation unit: generating said profiles for a plurality of said virtual users; further generating virtual user profiles having attribute information indicating characteristics of the plurality of virtual users based on the profiles of the plurality of virtual users; [1] The information processing device according to [1]. [3] The profile generation unit: estimating the attribute information characteristic of the plurality of virtual users by performing at least one of clustering and topic analysis on the profiles of the plurality of virtual users; [2] The information processing device according to [2]. [4] The behavior prediction unit changing a condition for providing the content in the virtual space in a plurality of ways, and predicting the behavior of the user in the real world based on the behavior of the virtual user; The information processing device according to any one of [1] to [3]. [5] The information processing device described in [4], wherein the provision conditions include at least one of the date, time, weather, location, congestion status of the location, provision manner of the provision content, and whether or not the virtual user is accompanied by someone. [6] The property information includes at least one of detailed information about the content provided, information about the target of the content provided, and information about the environment in which the content provided is provided. The information processing device according to any one of [1] to [5]. [7] The information processing device according to any one of [1] to [6], wherein the target content provided is different from the content provided to the user in the real world. [8] acquiring property information representing the property of the content provided, including at least one of a product and a service that can be provided to a user in the real world, and the content provided that the user in the real world has received; generating a profile of a virtual user based on the content provided to the user and the nature information corresponding to the content provided; A step of predicting the behavior of the user in the real world based on the behavior of the virtual user having the profile generated in the generating step with respect to the provided content of the target in the virtual space; An information processing method comprising:

[0063] [Explanation of terms, explanation of hardware configuration (Figure 4), etc.] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wires, wirelessly, etc.) and these multiple devices. The functional block may also be realized by combining the single device or multiple devices with software.

[0064] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocation, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0065] For example, an information processing device according to an embodiment of the present disclosure may function as a computer that executes the processes of the present disclosure. Fig. 4 is a diagram illustrating an example of a hardware configuration of an information processing device 10 according to an embodiment of the present disclosure. The information processing device 10 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0066] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the information processing device 10 may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0067] Each function of the information processing device 10 is realized by loading predetermined software (programs) onto hardware such as the processor 1001, memory 1002, etc., so that the processor 1001 performs calculations, controls communication via the communication device 1004, and controls at least one of reading and writing data in the memory 1002 and storage 1003.

[0068] The processor 1001 controls the entire computer by running, for example, an operating system, and may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc.

[0069] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-mentioned embodiments. Although the various processes have been described as being executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may be transmitted from a network via a telecommunications line.

[0070] The memory 1002 is a computer-readable recording medium and may be configured, for example, by at least one of a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0071] Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0072] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., to realize at least one of, for example, Frequency Division Duplex (FDD) and Time Division Duplex (TDD).

[0073] The input device 1005 is an input device (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (for example, a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (for example, a touch panel).

[0074] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0075] Furthermore, the information processing device 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0076] The notification of information is not limited to the aspects / embodiments described in the present disclosure and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI) and Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, and broadcast information (Master Information Block (MIB) and System Information Block (SIB))), other signals, or a combination thereof. Furthermore, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, or the like.

[0077] Each aspect / embodiment described in the present disclosure may be any of the following: LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (xG (x is, for example, an integer or decimal number)), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE The present invention may be applied to at least one of systems using 802.20, UWB (Ultra-Wideband), Bluetooth (registered trademark), or other appropriate systems, and next-generation systems that are extended, modified, created, or defined based on these systems. The present invention may also be applied to a combination of multiple systems (e.g., a combination of at least one of LTE and LTE-A with 5G).

[0078] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0079] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0080] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0081] Each aspect / embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Furthermore, notification of predetermined information (e.g., notification that "X is true") is not limited to being done explicitly, but may be done implicitly (e.g., by not notifying the predetermined information).

[0082] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0083] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0084] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0085] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0086] Note that terms explained in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

[0087] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0088] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by an index.

[0089] The names used for the above-described parameters are not intended to be limiting in any way. Furthermore, the mathematical expressions using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

[0090] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0091] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0092] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0093] When used in this disclosure, the terms "include," "including," and variations thereof are intended to be inclusive, similar to the term "comprising." Furthermore, when used in this disclosure, the term "or" is not intended to be an exclusive or.

[0094] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0095] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different." [Explanation of symbols]

[0096] 10...information processing device, 11...acquisition unit, 12...profile generation unit, 13...behavior prediction unit, 14...output unit, 30...virtual space control server, 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus.

Claims

1. an acquisition unit that acquires content provided to a user in the real world from content provided to the user in the real world, the content including at least one of a product and a service that can be provided to the user in the real world, and property information that represents the property of the content provided; a profile generation unit that generates a profile of a virtual user based on the provided content received by the user in the real world and the property information corresponding to the provided content; a behavior prediction unit that predicts the behavior of the user in the real world based on the behavior of the virtual user having the profile generated by the profile generation unit with respect to the provided content of the target in the virtual space; An information processing device comprising:

2. The profile generation unit generating said profiles for a plurality of said virtual users; further generating virtual user profiles having attribute information indicating characteristics of the plurality of virtual users based on the profiles of the plurality of virtual users; The information processing device according to claim 1 .

3. The profile generation unit estimating the attribute information characteristic of the plurality of virtual users by performing at least one of clustering and topic analysis on the profiles of the plurality of virtual users; The information processing device according to claim 2 .

4. The behavior prediction unit changing a provision condition of the content provided in the virtual space in a plurality of ways, and predicting the behavior of the user in the real world based on the behavior of the virtual user; The information processing device according to claim 1 .

5. The information processing device according to claim 4, wherein the provision conditions include at least one of the date, time period, weather, location, congestion status of the location, provision mode of the content, and whether the virtual user is accompanied by someone.

6. The property information includes at least one of detailed information about the content provided, information about a target of the content provided, and information about an environment in which the content provided is provided. The information processing device according to claim 1 .

7. The information processing device according to claim 1 , wherein the target content provided is different from the content provided to the user in the real world.

8. acquiring property information representing the property of the content provided, including at least one of a product and a service that can be provided to a user in the real world, and the content provided that has been received by the user in the real world; generating a profile of a virtual user based on the content provided to the user and the nature information corresponding to the content provided; A step of predicting the behavior of the user in the real world based on the behavior of the virtual user having the profile generated in the generating step with respect to the provided content of the target in the virtual space; An information processing method comprising:

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