JP7264847B2 - 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.

Conventionally, there is known a technique of predicting demand for a target corresponding to a query based on a query used by a user for searching and location information of the user at the time of searching by the query (see Patent Document 1).

JP 2019-53449 A

However, the conventional techniques described above cannot always effectively improve product sales.

The present application has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program that can effectively increase product sales.

An information processing apparatus according to the present application includes an acquisition unit that acquires a history of input information related to an event corresponding to a predetermined product, and a location where demand corresponding to the predetermined product may occur based on the history of the input information. and an estimating unit for estimating.

According to one aspect of the embodiment, it is possible to effectively increase product sales.

FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to the embodiment; FIG. 3 is a diagram illustrating a configuration example of an information processing apparatus according to the embodiment; 4 is a diagram illustrating an example of an action history storage unit according to the embodiment; FIG. FIG. 5 is a diagram illustrating an example of a search history storage unit according to the embodiment; 6 is a diagram illustrating an example of a business operator information storage unit according to the embodiment; FIG. FIG. 7 is a flowchart illustrating an information processing procedure according to the embodiment; FIG. 8 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus.

Hereinafter, modes for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. In addition, in the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

[1. Overview of information processing according to the embodiment]
First, an overview of information processing according to the embodiment will be described along the premise. For example, an event may have a demand for a product. That is, there may be a demand caused by an event. To give an example, it can be said that the demand for "sunscreen" products can be caused by the event "sunburn". In this way, an event and the demand for a certain product may correspond to each other in the relationship of cause and effect, so the demand for the product is generated by analyzing the user trends related to the event. It is believed that the location can be effectively specified.

For example, due to the spread of the Internet, when a user experiences a certain event or when it is known in advance that he or she will experience a certain event, it is not possible for the user to take action such as searching or posting about this event. There is Therefore, it can be said that there is a high possibility that a demand for a product corresponding to a certain event will occur in the vicinity of such an action. Also, for example, if this product (for example, a sample of the product) can be placed in a hotel or store located in a place where the demand for the product is likely to occur, the sales of the product can be effectively improved. It is possible.

Therefore, in this embodiment, focusing on the fact that events and product demand may correspond to each other in the relationship of cause and effect, based on the history of input information entered by users regarding events, product I got the idea of estimating the place where the demand corresponding to the

Specifically, in this embodiment, the following information processing is performed as the information processing according to the embodiment. For example, in this embodiment, a history of input information related to events corresponding to a given product is acquired. For example, in this embodiment, a search history including search queries related to this event is acquired as the history of input information. Then, in this embodiment, based on the history of the acquired input information, a place where a demand corresponding to a predetermined product may occur is estimated. For example, in the present embodiment, based on the location information of the user who made the input indicated by the input information history, the place where the demand corresponding to the predetermined product may occur is estimated.

Also, in the present embodiment, a proposal for a given product is made based on the estimated location. For example, in this embodiment, when a predetermined service provider exists in the estimated location, the predetermined service provider is proposed as a candidate who handles a predetermined product. For example, in this embodiment, a predetermined service provider is proposed as a candidate for handling this predetermined product to a business operator that provides a predetermined product.

Then, according to the information processing according to such an embodiment, it becomes possible to effectively improve product sales. In this embodiment, the place where the demand corresponding to the predetermined product may occur may include the concept of the place where the phenomenon corresponding to the predetermined product may occur.

[2. Information processing system according to the embodiment]
Before describing FIG. 1, an information processing system according to an embodiment will be described with reference to FIG. FIG. 2 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. The information processing system 1 according to the embodiment includes a user device 10, a business operator device 30, and an information processing device 100, as shown in FIG. The user device 10, the provider device 30, and the information processing device 100 are communicably connected via a network N by wire or wirelessly. The information processing system 1 shown in FIG. 2 may include a plurality of user devices 10, a plurality of provider devices 30, and a plurality of information processing devices 100. FIG.

The user device 10 is an information processing terminal used by a user (end user). The user device 10 is, for example, a smart phone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like.

The business operator device 30 is an information processing terminal that is used by a business operator that joins the information processing system 1 according to the embodiment and seeks a proposal for the most suitable supplier of its company's products. The business operator device 30 is, for example, a smart phone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like.

The information processing device 100 is an information processing device that performs information processing according to the embodiment, and is realized by a server device, a cloud system, or the like. In this embodiment, the information processing device 100 is assumed to be a server device.

[3. About the event]
An event according to an embodiment may be, for example, any event that has a physical or mental impact on a user and that increases the demand for a particular product. For example, the events according to the embodiment may correspond to physical symptoms caused by internal or external factors, weather, traffic conditions, and various situations in daily life. Further, later, by the analysis processing described in step S11 of FIG. 1, it may be found that the demand for a specific product is caused by an event that was not anticipated until now. Therefore, the event according to the embodiment is not limited to a specific event.

[4. Example of information processing according to the embodiment]
An example of information processing according to the embodiment will now be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. Also, in FIG. 1, the product is assumed to be a physical product that may be handled by various service providers such as hotels and shops.

First, based on the user's context, the information processing apparatus 100 analyzes what types of products are in demand for what events (step S11). For example, the information processing apparatus 100 acquires information indicating in what context (state) the behavior indicated by the behavior information of the user was performed. For example, the information processing apparatus 100 acquires information indicating in what context (state) the action indicated by the action information (action history) regarding purchase was performed.

As will be described later, the action history storage unit 121 (FIG. 4) stores, for each user, "context information" and "action information" of the user in association with each other. Therefore, the information processing apparatus 100 accesses the action history storage unit 121 and stores "context information" and "action information" as information indicating in what context (state) the action indicated by the action information of the user was performed. Get each combination with .

Based on the combination of the "context information" and the "behavior information", the information processing apparatus 100 determines what type of product the user tends to purchase under what context. By analyzing (learning) the relationship between product types, it is possible to analyze the demand trends for what types of products for what events. For example, the information processing apparatus 100 estimates, from the context, the event of the factor indicating the context, and analyzes the trend of demand for what type of product for what event.

In the example of FIG. 1, users U1, U2, and U3 are illustrated as examples of users whose context information is used. Of course, the number of users for whom context information is acquired does not have to be three as in FIG.

In the example of FIG. 1, "context #1" and "behavior information #1-1" are associated with user U1. In this example, the user U1 performs the action indicated by the action information "action information #1-1" in the state indicated by the "context #1". In the example of FIG. 1, "context #2" and "behavior information #2-1" are associated with user U2. In this example, the user U2 performs the action indicated by the action information "action information #2-1" in the state indicated by the "context #2". In the example of FIG. 1, "context #3" and "behavior information #3-1" are associated with user U3. In this example, the user U3 performs the action indicated by the action information "action information #3-1" in the state indicated by the "context #3".

Therefore, in the example of FIG. 1, the information processing apparatus 100 combines the "context information" and "behavior information" corresponding to the user U1, the "context information" and "behavior information" corresponding to the user U2. , and a combination of "context information" and "behavior information" corresponding to user U3. Further, the information processing apparatus 100 analyzes what type of product the user tends to purchase in what kind of context, based on the acquired three sets. In other words, the information processing apparatus 100 analyzes the trend of demand for what type of product for what kind of event based on the acquired three sets.

In the example of FIG. 1, the information processing apparatus 100 obtains the analysis result that there is a demand for the product of "product type TY1" for "phenomenon EV1" from the analysis in step S11. In such an example, the product of "product type TY1" is an example of a predetermined product, and "event EV1" is an example of an event corresponding to the predetermined product. Further, here, for example, assuming that the event EV1 is "sunburn" and the product type TY1 is "sunscreen", in the example of FIG. It can be said that the analysis results indicate that there is demand for the product.

Next, the information processing apparatus 100 identifies a search query regarding the event EV1 (step S12). The information processing device 100 can identify the search query using any method. For example, if a search query related to the event is specified for information indicating a representative event, the information processing device 100 can specify the search query related to the event EV1 according to this specification. . Further, the information processing apparatus 100 may specify a keyword (eg, "sunscreen") including part or all of the information (eg, "sunburn") indicating the event EV1 as the search query regarding the event EV1.

Further, the information processing apparatus 100 may identify a similar word of information indicating the event EV1 (for example, "sunburn") as a search query regarding the event EV1. When searching for products, the user may directly enter a search query or specify a search query (category for narrowing down) at a predetermined shopping site or a predetermined EC site. Therefore, the information processing apparatus 100 may identify the search query related to the event EV1 among the search queries used by the user by referring to the search history corresponding to these sites.

Next, the information processing apparatus 100 accesses the search history storage unit 122 (FIG. 5) and acquires the search history including the search query (search query regarding the event EV1) specified in step S12 (step S13). Note that the search history storage unit 122 stores, for each user, a search history obtained by searching for products on a shopping site operated by a business operator (referred to as "business operator T") corresponding to the information processing device 100. It is assumed that

Also, for example, if the information processing apparatus 100 specifies "sunscreen" as a search query related to event EV1, as shown in FIG. Acquired from the unit 122 . In the example of FIG. 1 , the information processing apparatus 100 determines that the user identified by the user ID (identifier) “U10” is identified by “search date and time #10” as the search history including the search query “sunscreen”. An example of obtaining a search history #1 indicating that a search was performed using a search query “sunscreen” at a search location indicated by “search location #10” at time is shown.

Further, in the example of FIG. 1, the information processing apparatus 100 determines that the user identified by the user ID (identifier) "U11" is "search date and time #11" as the search history including the search query "sunscreen". shows an example of obtaining a search history #1 indicating that a search was performed using the search query "sunscreen" at the search location indicated by "search location #11" at the time indicated by .

Note that the search history #1 shown in FIG. 1 includes only two users, users U10 and U11, as users who searched for the search query related to the event EV1. users may be included.

Next, the information processing apparatus 100 finds the search location of the user who performed the search (search using the search query related to the event EV1) indicated by the search history #1 (the user who performed the input indicated by the input information history). (an example of the position information of )), the location where the demand corresponding to the product of the product type TY1 may occur is estimated (step S14).

For example, the information processing apparatus 100 estimates a location where a demand corresponding to the product of the product type TY1 may occur, based on the location searched by the user when the search indicated by the search history #1 was performed. For example, the information processing apparatus 100 estimates the area corresponding to the search location of the user when the search indicated by the search history #1 was performed as a place where demand corresponding to the product of the product type TY1 may occur. .

For example, the information processing apparatus 100 determines that the search indicated by the search history #1 was performed more frequently in the area corresponding to the search location of the user when the search indicated by the search history #1 was performed. Areas with tendencies are estimated as places where demand corresponding to products of product type TY1 may occur. For example, information processing apparatus 100 assigns an area that includes more search locations to products of product type TY1 among areas corresponding to search locations of the user when the search indicated by search history #1 is performed. Estimated as where the corresponding demand could occur. That is, the information processing apparatus 100 estimates a place where demand corresponding to the product of the product type TY1 is likely to occur, based on the tendency of the location indicated by the location information of the user who performed the search. In the example of FIG. 1, the search locations of the user when the search indicated by search history #1 was performed are the search location indicated by "search location #10" and the search location indicated by "search location #11". is the search location shown.

Further, information processing apparatus 100 executes this search at a predetermined point in time before the search indicated by search history #1 is performed (for example, at a predetermined point in time up to one hour before the search is performed). The area corresponding to the stay position where the user who visited may be estimated as a place where the demand corresponding to the product of the product type TY1 may occur.

To give an example, information processing apparatus 100 determines, at a predetermined time before the search indicated by search history #1, the area corresponding to the stay position where the user who performed this search stayed. Of these areas, areas that include more staying positions are estimated as places where demand for products of the product type TY1 can occur. That is, the information processing apparatus 100 estimates a place where demand corresponding to the product of the product type TY1 is likely to occur, based on the tendency of the location indicated by the location information of the user who performed the search.

For example, when users can predict in advance that they will experience a specific event at their destination, they tend to try to obtain a product for dealing with this event before their destination. According to the information processing apparatus 100 according to the embodiment, it is possible to estimate an area corresponding to a position where a user may have stayed to obtain a product for event countermeasures. By proposing to the product provider to put the product in a hotel, store, or the like, it is possible to effectively increase the sales of the product.

Further, information processing apparatus 100 performs this search at a predetermined time after the search indicated by search history #1 (for example, at a predetermined time up to one hour after the search was performed). The area corresponding to the stay position where the user was staying may be estimated as a place where the demand corresponding to the product of the product type TY1 may occur.

For example, at a predetermined time after the search indicated by search history #1 has been performed, information processing apparatus 100 stores , an area containing more staying positions is estimated as a place where a demand corresponding to the product of the product type TY1 can occur. That is, the information processing apparatus 100 estimates a place where demand corresponding to the product of the product type TY1 is likely to occur, based on the tendency of the location indicated by the location information of the user who performed the search.

For example, after experiencing a particular event, a user may travel to obtain a product to reduce the effects (eg, physical effects) of the particular event. According to the information processing apparatus 100 according to the embodiment, it is possible to estimate the area corresponding to the position where the user may have stayed after experiencing the event in an attempt to obtain a product for reducing the impact of the event. , by proposing to the product provider that the product should be placed in a hotel or store located in such an area, the sales of the product can be effectively increased.

Note that the information processing apparatus 100 compares, for example, the user's location information history with the user's search location when the search indicated by the search history #1 was performed, thereby determining the length of stay for each user. can be located.

Next, the information processing apparatus 100 determines whether or not a predetermined service provider exists at the location estimated in step S14. (step S15). In the example of FIG. 1, "Hotel HT", which operates nationwide, is taken as an example of the predetermined service provider. Also, in step S14, the information processing apparatus 100 presumes the "area AR" as a place where a demand corresponding to the product of the product type TY1 may occur.

In such an example, the information processing device 100 determines whether or not the hotel HT exists in the area AR. Then, for example, when the information processing apparatus 100 can determine that the hotel HT exists in the area AR, as a candidate handling the product of the product type TY1 (for example, a sample corresponding to the product of the product type TY1), A hotel HT existing in this area AR is determined among the hotels HT all over the country. Further, the information processing apparatus 100 provides products belonging to the category of the product type TY1 among the business operators who request the proposal of the optimum handling destination of their own products by joining the information processing system 1 according to the embodiment ( (manufacturer) is identified. For example, the information processing apparatus 100 refers to the business operator information storage unit 123 (FIG. 6) to identify the business operator that provides products belonging to the category of product type TY1.

Here, assuming that the information processing apparatus 100 identifies the business operator BP1 as the business operator that provides the product of the product type TY1, as shown in FIG. A hotel HT located in the area AR is proposed as a candidate to be handled. For example, the information processing device 100 transmits, to the business operator device 30 of the business operator BP1, recommendation information recommending placing a free sample corresponding to the product of the product type TY1 in the hotel HT located in the area AR.

According to this example, the demand for products of product type TY1 is increasing at hotel HT located in area AR. inevitably higher. As a result, since the product of the business operator BP1 and of the product type TY1 is effectively advertised, there is a high possibility that the sales of such product will increase. As such, the information processing apparatus 100 according to the embodiment can effectively increase product sales.

[5. Variations of information processing according to the embodiment]
The information processing apparatus 100 according to the above embodiment may be implemented in various different forms other than the above embodiment. Therefore, other embodiments of the information processing apparatus 100 will be described below.

[5-1. Acquisition of history]
As a simple example, FIG. 1 illustrates an example in which the information processing apparatus 100 acquires a search history including search queries related to the event EV1. However, the information processing apparatus 100 may acquire, from among the search histories including search queries related to the event EV1, the histories in which a plurality of different users have a common search timing. For example, the information processing apparatus 100 acquires, from among the search histories including search queries related to the event EV1, the histories corresponding to timings at which searches were performed by a predetermined number or more of users.

For example, by analyzing search history #1, information processing apparatus 100 determines the time period in which searches (searches with search queries related to event EV1) indicated by search history #1 were performed by a predetermined number or more of users. Identify. For example, it is assumed that information processing apparatus 100 specifies that searches indicated by search history #1 have been performed by a predetermined number or more of users during the “time period from 13:00 to 15:00”. In this case, information processing apparatus 100 further acquires the search history corresponding to the "time period from 13:00 to 15:00" from search history #1, and the location information of the user who performed the search indicated by this search history. Based on , the place where the demand corresponding to the product of the product type TY1 can occur is estimated.

According to the information processing apparatus 100 as described above, it is possible to estimate a place where a demand corresponding to a predetermined product is likely to occur while focusing on location information of users who are more likely to need the predetermined product. can improve estimation accuracy.

[5-2. Regarding the history of input information]
In the example of FIG. 1, the information processing apparatus 100 acquires a search history including search queries related to events as a history of input information. However, the information processing apparatus 100 may acquire, as the history of input information, a history of posting to a predetermined service (for example, SNS) that includes a keyword related to an event.

[6. Configuration of Information Processing Device]
Next, the information processing apparatus 100 according to the embodiment will be described using FIG. FIG. 3 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 3, the information processing apparatus 100 has a communication section 110, a storage section 120, and a control section .

(Regarding communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits/receives information to/from the user device 10 or the business operator device 30, for example.

(Regarding storage unit 120)
The storage unit 120 is realized by, for example, a RAM (Random Access Memory), a semiconductor memory device such as a flash memory, or a storage device such as a hard disk or an optical disk. Storage unit 120 includes action history storage unit 121 , search history storage unit 122 , and business operator information storage unit 123 .

(Regarding the action history storage unit 121)
The action history storage unit 121 stores action information (action history) indicating actions of the user. Here, FIG. 4 shows an example of the action history storage unit 121 according to the embodiment. In the example of FIG. 4, the action history storage unit 121 has items such as "user ID (Identifier)", "user information", "context information", "action information", and "date and time information".

"User ID" indicates identification information for identifying a user. "User information" is information indicating various attributes such as the user's name, sex, age, hobbies and preferences, demographic attributes and psychographic attributes of the user. The “context information” is information indicating in what context (state) the action indicated by the associated action information was performed. Also, "behavior information" is information indicating the behavior of the user. The "date and time information" is information indicating the date and time when the action indicated by the associated action information was performed or the date and time when the action information was acquired.

That is, in the example of FIG. 4, various attributes of the user indicated by the user ID "U1" indicate that the user information is "user information #1". Further, such information is such that the user indicated by the user ID "U1" performs the action indicated by the action information "action information #1-1" in the state indicated by the context information "context #1". An example of performing at the date and time indicated by "date and time information #1-1" is shown.

Any information other than the information shown in FIG. 4 may be stored in the action history storage unit 121 . In addition, in the example of FIG. 4, conceptual values such as "U1", "user information #1", "context #1", "behavior information #1-1", and "date and time information #1-1" are described. However, in reality, character strings and numbers to identify users, character strings to indicate user attributes, character strings and numbers to identify contexts, numbers and characters to indicate user behavior, or A character string entered by the user, a numerical value indicating the date and time, and the like are registered.

(Regarding the search history storage unit 122)
The search history storage unit 122 stores user history. In this embodiment, the search history storage unit 122 stores, for each user, the search history of products searched for on the shopping site operated by the business operator T, but the search history storage unit 122 may store a search history of any content searched for.

Here, FIG. 5 shows an example of the search history storage unit 122 according to the embodiment. In the example of FIG. 5, the action history storage unit 121 has items such as "user ID (Identifier)", "history ID", "search date and time", "search query", and "search location".

"User ID" indicates identification information for identifying a user who has performed a search using the corresponding history ID. The “history ID” indicates identification information for identifying a search history, with a set of corresponding search date/time, search query, and search location as one search history.

"Search date and time" indicates the date and time when the search identified by the corresponding history ID was performed. "Search query" indicates the search query used in the search identified by the corresponding history ID. “Search location” indicates the location (position) where the search identified by the corresponding history ID was performed.

For example, when receiving an input of a search query from the user, the user device 10 sends the received search query and location information (for example, GPS-derived location information) indicating the location where the search was performed with this search query. to the information processing apparatus 100 in a state of being associated with the user ID. Thereby, the information processing apparatus 100 can acquire the position information indicating the search location. When receiving a set of a user ID and a search query, the information processing device 100 accesses the user device 10 of the user identified by the user ID, and acquires position information indicating the search location. You may

Further, in the example of FIG. 5, the user (user U10) identified by the user ID "U10", at the time indicated by "search date and time #10", at the search location indicated by "search location #10", An example of a search using the search query "sunscreen" is shown. Further, the example of FIG. 5 shows an example in which search histories indicating such searches are identified by the history ID "#1-1".

Further, in the example of FIG. 5, conceptual data such as "U1", "history ID #1-1", "search date and time #1-1", "search query #1-1", and "search location #1-1" are used. However, in practice, appropriate numerical values are registered.

(Business operator information storage unit 123)
The business operator information storage unit 123 has a predetermined contract with a business operator (business operator T) who seeks a proposal for an optimal handling destination for its company's products by subscribing to the information processing system 1 according to the embodiment. Stores information about business operators as customers). Here, FIG. 6 shows an example of the business operator information storage unit 123 according to the embodiment. In the example of FIG. 6, the business operator information storage unit 123 has items such as "business operator ID (Identifier)", "name", "category", and "location".

"Business ID" indicates identification information for identifying a business that seeks a proposal for an optimum handling destination for its company's products by subscribing to the information processing system 1 according to the embodiment. "Name" indicates the name of the company identified by the corresponding company ID. For example, "name" is a corporate name, a sole proprietor name, or the like. "Category" is information indicating what category of product the business operator identified by the corresponding business operator ID provides. For example, if the company manufactures and sells cosmetics, "cosmetics" is registered as the category.

That is, in the example of FIG. 6, the name of the business operator (business operator BP1) identified by the business operator ID 'BP1' is 'name #1', and the relevant business operator belongs to the category 'category #1'. Here is an example of manufacturing and selling again. In the example of FIG. 6, the location of business operator BP1 is "location #1". In the example of FIG. 6, conceptual values such as "BP1", "name #1", "category #1", and "location #1" are described, but in reality, appropriate numerical values indicating these will be registered.

(Regarding the control unit 130)
Returning to FIG. 3, the control unit 130 executes various programs stored in a storage device inside the information processing apparatus 100 using a RAM as a work area by means of a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. It is realized by Also, the control unit 130 is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 3, the control unit 130 includes an analysis unit 131, an acquisition unit 132, an estimation unit 133, and a proposal unit 134, and implements 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. 3, and may be another configuration as long as it performs information processing described later. Moreover, the connection relationship between the processing units of the control unit 130 is not limited to the connection relationship shown in FIG. 3, and may be another connection relationship.

(Regarding the analysis unit 131)
The analysis unit 131 analyzes what kind of product is in demand for what kind of event based on the user's context. For example, the analysis unit 131 accesses the action history storage unit 121 and stores “context information” and “action information” as information indicating in what context (state) the action indicated by the action information of the user was performed. get each combination of

Based on the combination of the “context information” and the “behavior information,” the analysis unit 131 determines what type of product the user tends to purchase under what context. By analyzing (learning) the relationship between types, it is possible to analyze the demand trends for what types of products for what events. For example, the analysis unit 131 estimates, from the context, the event of the factor that indicates the context, and analyzes what type of product demand trend exists for the estimated event. That is, the analysis unit 131 identifies a combination of an event and a product that have a cause-effect relationship based on the user's context.

(Regarding the acquisition unit 132)
The acquisition unit 132 acquires a history of input information regarding events corresponding to a predetermined product. For example, the acquisition unit 132 acquires a history of input information related to an event that requires a predetermined product as an event corresponding to the predetermined product based on the analysis result by the analysis unit 131 . For example, when a combination of an event and a product having a cause-effect relationship is obtained by the analysis processing by the analysis unit 131, the acquisition unit 132 acquires the history of input information related to this event. For example, the acquisition unit 132 acquires a search history including a search query regarding an event as a history of input information.

In addition, the acquiring unit 132 outputs the information indicating the product corresponding to this event (the product that is found to be in demand due to the event) to the estimating unit 133 in association with the history of the acquired input information. .

In the example of FIG. 1, the analysis unit 131 obtains the analysis result that there is a demand for the product of "product type TY1" for "event EV1". Therefore, in the example of FIG. 1, the acquisition unit 132 identifies the search query regarding the event EV1 based on such an analysis result, and searches for the search history #1 including the identified search query (search query regarding the event EV1). It is acquired from the history storage unit 122 . Further, in this example, the obtaining unit 132 outputs the product information indicating the product of the “product type TY1” and the search history #1 in association with each other to the estimating unit 133 .

Further, as described as a variation of the information processing corresponding to FIG. 1, the acquisition unit 132 acquires, from among the histories of input information, the histories in which the timings of inputs are common among a plurality of different users. may For example, the acquisition unit 132 may acquire a history corresponding to a timing when a predetermined number or more of users input information from the history of input information.

Using the example of FIG. 1, the acquisition unit 132 analyzes the search history #1 to find that a predetermined number or more of users have performed searches indicated by the search history #1 (searches with search queries related to the event EV1). Identify the time period during which the For example, if the obtaining unit 132 identifies that a predetermined number or more of users performed searches indicated by search history #1 in the “time period from 13:00 to 15:00,” The search history corresponding to the "time period from 13:00 to 15:00" is further acquired. Then, the acquiring unit 132 outputs the acquired search history to the estimating unit 133 so as to estimate a place where demand may occur based on the acquired search history.

In addition, by analyzing search history #1, acquisition unit 132 finds that the largest number of users in each time period perform searches indicated in search history #1 (searches with search queries related to event EV1). You may specify the time period. For example, if the acquiring unit 132 identifies that the search indicated by the search history #1 was performed by the largest number of users at “13:00”, the acquisition unit 132 determines Get more corresponding search history.

The acquisition unit 132 can also acquire target information stored in the action history storage unit 121 and target information stored in the search history storage unit 122 . For example, the acquisition unit 132 acquires these pieces of information from any external device (for example, a server device related to the information processing device 100), associates them with the user ID, and can be registered with

(Regarding the estimation unit 133)
The estimating unit 133 estimates locations where demand corresponding to a predetermined product may occur, based on the history of input information. For example, when the estimating unit 133 receives from the estimating unit 133 information indicating a product corresponding to an event (a product found to be in demand due to the event) and a history of input information related to this event, the estimating unit 133 Estimate where demand corresponding to a product (a given product) can occur.

For example, the estimating unit 133 estimates a place where a demand corresponding to a predetermined product may occur, based on the location information of the user who has performed the input indicated by the input information history. For example, the estimating unit 133 estimates a place where a demand corresponding to a predetermined product is likely to occur, based on the positional tendency indicated by the user's positional information.

For example, the estimation unit 133 estimates an area corresponding to the position of the user when the input indicated by the input information history is performed as a place where demand corresponding to a predetermined product may occur. In the example of FIG. 1, the estimating unit 133 determines whether the search indicated by the search history #1 was performed in the area corresponding to the search location of the user when the search indicated by the search history #1 was performed. Areas with tendencies are estimated as places where demand corresponding to products of product type TY1 may occur. For example, of the areas corresponding to the search locations of the user when the search indicated by the search history #1 was performed, the estimating unit 133 associates an area containing more search locations with the product of the product type TY1. It is estimated as a place where demand for

Also, for example, the estimating unit 133 associates an area corresponding to the stay position where the user stayed at a predetermined point in time before the input indicated by the history of input information is performed as a predetermined product. You may estimate as a place where demand may occur. For example, estimating unit 133 determines, at a predetermined point in time before the search indicated by search history #1 is performed, more of the area corresponding to the stay position where the user who performed this search stayed. is estimated as a place where a demand corresponding to the product of the product type TY1 may occur.

Also, for example, the estimating unit 133 determines the area corresponding to the stay position where the user was staying at a predetermined point in time after the input indicated by the history of the input information is performed, as a demand corresponding to a predetermined product. can be estimated as a place where For example, estimating unit 133 determines, at a predetermined point in time before the search indicated by search history #1 is performed, more of the area corresponding to the stay position where the user who performed this search stayed. is estimated as a place where a demand corresponding to the product of the product type TY1 may occur.

(Regarding the proposal section 134)
The proposing unit 134 makes a proposal regarding a predetermined product based on the location estimated by the estimating unit 133 . For example, when a predetermined service provider exists in the location estimated by the estimation unit 133, the proposing unit 134 proposes the predetermined service provider as a candidate who handles a predetermined product. For example, the proposal unit 134 proposes a predetermined service provider as a candidate who handles a predetermined product to a business operator that provides a predetermined product.

In the example of FIG. 1, the proposal unit 134 determines whether a hotel HT (an example of a predetermined service provider) exists in the area AR (an example of the location estimated by the estimation unit 133). Then, for example, when it is determined that a hotel HT exists in the area AR, the proposal unit 134 selects hotel HTs existing in this area AR among hotel HTs nationwide as candidates for handling products of the product type TY1. to decide. In addition, the proposal unit 134 provides products belonging to the category of product type TY1 (manufacturer to identify the operator. For example, the proposal unit 134 refers to the business operator information storage unit 123 (FIG. 6) to identify the business operator that provides products belonging to the category of product type TY1.

In such a state, if the proposal unit 134 identifies the business operator BP1 as a business operator that provides products of the product type TY1, the proposal unit 134 identifies the business operator BP1 as a candidate that handles the products of the product type TY1. A hotel HT located in the area AR is proposed. For example, the proposal unit 134 transmits, to the business operator device 30 of the business operator BP1, recommendation information recommending placing a free sample corresponding to the product of the product type TY1 in the hotel HT in the area AR.

[7. Processing procedure]
Next, the procedure of information processing according to the embodiment will be described with reference to FIG. FIG. 7 is a flowchart illustrating an information processing procedure according to the embodiment;

First, the analysis unit 131 analyzes what kind of product is in demand for what kind of event based on the context of the user (step S101). For example, the analysis unit 131 estimates from the context of the user the event of the factor that indicates the context, and analyzes what kind of product demand trend exists for the estimated event. do. That is, the analysis unit 131 identifies a combination of an event and a product that have a cause-effect relationship based on the user's context.

Next, the acquisition unit 132 identifies a search query related to an event identified (determined) as a cause of demand in the analysis result of the analysis processing in step S101 (step S102).

The acquisition unit 132 also acquires the search history including the specified search query from the search history storage unit 122 (step S103). Also, although not shown in FIG. 7, the acquisition unit 132 provides information indicating a product corresponding to an event identified (determined) as a cause of demand (a product found to be in demand due to the event), It is output to the estimation unit 133 in a state of being associated with the search history including the search query regarding this event.

Next, the estimation unit 133 estimates locations where demand for the product corresponding to the phenomenon may occur based on the search location of the user who performed the search indicated in the search history acquired in step S103 (step S104). ). For example, the estimating unit 133 estimates a location where demand for the product corresponding to the event may occur, based on the tendency of search locations by users.

Next, the proposal unit 134 determines whether or not a predetermined service provider exists at the location estimated in step S104 (step S105). If the proposal unit 134 determines that the predetermined service provider does not exist at the location estimated in step S104 (step S105; No), the process ends.

On the other hand, when the proposal unit 134 determines that a predetermined service provider exists at the location estimated in step S104 (step S105; Yes), it makes a proposal regarding a product corresponding to the event (step S106). . For example, when proposing unit 134 determines that a predetermined service provider exists, it determines this predetermined service provider as a candidate for handling the product corresponding to the event. In addition, the proposal unit 134 provides a product corresponding to an event (manufacturer) among business operators who request a proposal for an optimum handling destination of their company's product by joining the information processing system 1 according to the embodiment. Identify the business. Then, the proposal unit 134 transmits to the business operator device 30 of the identified business operator recommendation information recommending that a predetermined service provider place a free sample of the product corresponding to the event.

[8. Hardware configuration]
Further, the information processing apparatus 100 according to the above embodiment is implemented by a computer 1000 configured as shown in FIG. 8, for example. FIG. 8 is a hardware configuration diagram showing an example of a computer 1000 that implements the functions of the information processing apparatus 100. As shown in FIG. Computer 1000 has CPU 1100 , RAM 1200 , ROM 1300 , HDD 1400 , communication interface (I/F) 1500 , input/output interface (I/F) 1600 and media interface (I/F) 1700 .

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

HDD 1400 stores programs executed by CPU 1100 and data used by these programs. Communication interface 1500 receives data from other devices via communication network 50 and sends the data to CPU 1100 , and transmits data generated by CPU 1100 to other devices via communication network 50 .

The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, through an input/output interface 1600 . CPU 1100 acquires data from an input device via input/output interface 1600 . CPU 1100 also outputs the generated data to an output device via input/output interface 1600 .

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

For example, when the computer 1000 functions as the information processing apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the functions of the control unit 130 by executing programs loaded on the RAM 1200 . In addition, data in storage unit 120 is stored in HDD 1400 . CPU 1100 of computer 1000 reads these programs from recording medium 1800 and executes them, but as another example, these programs may be obtained from another device via communication network 50 .

[9. others〕
Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

As described above, the embodiments of the present application have been described in detail based on several drawings, but these are examples, and various modifications and It is possible to carry out the invention in other forms with modifications.

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

1 information processing system 10 user device 30 provider device 100 information processing device 120 storage unit 121 action history storage unit 122 search history storage unit 123 provider information storage unit 130 control unit 131 analysis unit 132 acquisition unit 133 estimation unit 134 proposal unit

Claims (13)

an analysis unit that analyzes what kind of product is in demand for what kind of event based on the user's context;
Input information entered by the user regarding an event that the first product is required as an event corresponding to the first product, which is a product found to be in demand based on the analysis result by the analysis unit. an acquisition unit that acquires the history of
an estimating unit for estimating a place where a demand corresponding to the first product is likely to occur, based on location information of a user who has made an input indicated by the history of the input information. Device. The information processing apparatus according to claim 1 , wherein the acquisition unit acquires a search history including a search query regarding the event as the history of the input information. 3. The information processing apparatus according to claim 1 , wherein the acquisition unit acquires, from among the histories of the input information, a history in which a plurality of different users have a common input timing. . 4. The information processing apparatus according to claim 3 , wherein the acquisition unit acquires, from among the history of the input information, a history corresponding to a timing when a predetermined number or more of users have input. 4. The information processing according to claim 3 , wherein the estimating unit estimates a place where demand corresponding to the first product may occur, based on a tendency of location indicated by the location information of the user. Device. The estimating unit estimates an area corresponding to the position of the user when the input indicated by the history of the input information is performed as a place where demand corresponding to the first product may occur. 6. The information processing apparatus according to any one of claims 1 to 5 . The estimating unit associates an area corresponding to a stay position where the user stayed at a predetermined time before the input indicated by the history of the input information is performed as the first product. The information processing apparatus according to any one of claims 1 to 6, wherein the location is estimated as a place where demand may occur. The estimating unit determines, at a predetermined point in time after the input indicated by the history of the input information is performed, the area corresponding to the stay position where the user has stayed, as the demand corresponding to the first product. 8. The information processing apparatus according to any one of claims 1 to 7, characterized in that it is estimated as a place where a is likely to occur. The information processing apparatus according to any one of claims 1 to 8 , further comprising a proposing unit that makes a proposal regarding the first product based on the location estimated by the estimating unit. The proposing unit, if a predetermined service provider exists at the location estimated by the estimating unit, proposes the predetermined service provider as a candidate for handling the first product. The information processing apparatus according to claim 9 . 11. The information according to claim 10 , wherein said proposal unit proposes said predetermined service provider as a candidate for handling said first product to a business operator that provides said first product. processing equipment. An information processing method executed by an information processing device,
an analysis step of analyzing what kind of product is in demand for what kind of event based on the user's context;
Input information entered by the user regarding an event that the first product is required as an event corresponding to the first product, which is a product found to be in demand based on the analysis result of the analysis step. an acquisition step of acquiring the history of
an estimating step of estimating a place where demand corresponding to the first product is likely to occur, based on location information of a user who has made an input indicated by the history of the input information. Method. an analysis procedure for analyzing what kind of product is in demand for what kind of event based on the user's context;
Input information entered by the user regarding an event that the first product is required as an event corresponding to the first product, which is a product found to be in demand based on the analysis results of the analysis procedure. an acquisition procedure for acquiring the history of
an estimation procedure for estimating a location where demand corresponding to the first product is likely to occur, based on the location information of the user who made the input indicated by the history of the input information; information processing program.

Images