JP2020115279A - Estimation apparatus, estimation method and estimation program - Google Patents

Abstract

To promote improvement in usability.SOLUTION: An estimation apparatus according to the present application includes an acquisition unit and an estimation unit. The acquisition unit acquires posted information of a user in relation to a predetermined transaction target and attribute information indicating an attribute of the user. The estimation unit estimates an attribute of the predetermined transaction target based on the posted information and the attribute information acquired by the acquisition unit.SELECTED DRAWING: Figure 1

Description

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

Conventionally, there is known a technique of generating structural data from unstructured data that is not structured by attributes and attribute values by a process of extracting information using a combination of attributes and attribute values.

International Publication No. 2014/167647

However, the above-mentioned conventional technique cannot always promote the improvement of usability.

The present application has been made in view of the above, and an object thereof is to promote improvement in usability.

The estimation device according to the present application includes an acquisition unit that acquires post information of a user with respect to a predetermined transaction target and attribute information indicating an attribute of the user, and the post information and the attribute information acquired by the acquisition unit. Based on the above, an estimating unit for estimating an attribute of the predetermined transaction object is provided.

According to the aspect of the embodiment, it is possible to promote the improvement of usability.

FIG. 1 is a diagram illustrating an example of an estimation process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the estimation system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the terminal device according to the embodiment. FIG. 4 is a diagram illustrating a configuration example of the estimation device according to the embodiment. FIG. 5 is a diagram illustrating an example of the posted information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of the user information storage unit according to the embodiment. FIG. 7 is a diagram illustrating an example of the estimated information storage unit according to the embodiment. FIG. 8 is a diagram illustrating a configuration example of the shopping server according to the embodiment. FIG. 9 is a flowchart showing an example of the estimation process according to the embodiment. FIG. 10 is a flowchart showing an example of the estimation process according to the embodiment. FIG. 11 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the estimation device.

Hereinafter, modes (hereinafter, referred to as “embodiments”) for carrying out the estimation device, the estimation method, and the estimation program according to the present application will be described in detail with reference to the drawings. It should be noted that the estimation device, the estimation method, and the estimation program according to the present application are not limited by this embodiment. Also, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicated description will be omitted.

(Embodiment)
[1. Example of estimation processing]
First, an example of the estimation process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of an estimation process according to the embodiment. FIG. 1 shows an example in which the estimation process according to the embodiment is executed by the estimation device 100.

[Configuration of information processing system]
Prior to the description of FIG. 1, the configuration of the estimation system 1 will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the estimation system according to the embodiment. As shown in FIG. 2, the estimation system 1 includes a terminal device 10, an estimation device 100, and a shopping server 200. The terminal device 10, the estimation device 100, and the shopping server 200 are connected via a predetermined network N so that they can communicate with each other in a wired or wireless manner. Note that the estimation system 1 illustrated in FIG. 2 may include a plurality of terminal devices 10, a plurality of estimation devices 100, and a plurality of shopping servers 200.

The terminal device 10 is an information processing device used by a user (hereinafter, appropriately referred to as “user”) who posts review information (hereinafter, appropriately referred to as “post information”) regarding a predetermined product. Here, the predetermined product is an example of a transaction target (hereinafter, appropriately referred to as “target”). In addition, the terminal device 10 is operated by a user (hereinafter appropriately referred to as “other user” or “other user”) who requests distribution of product information of a predetermined product (hereinafter appropriately referred to as “product page”). This is an information processing device used. The terminal device 10 is realized by a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. In the example illustrated in FIG. 1, the terminal device 10 is a smartphone.

The estimation device 100 is, for example, an information processing device such as a PC or WS (Work Station), and performs processing based on the information transmitted from the shopping server 200 via the network N.

The shopping server 200 is, for example, an information processing device such as a PC or WS, and distributes product information via the network N.

Although the estimation device 100 and the shopping server 200 are separate devices in FIG. 2, the estimation device 100 and the shopping server 200 may be integrated. Further, the estimation device 100 and the shopping server 200 may be managed by the same administrator.

Before returning to the description of FIG. 1, a comparison between the estimation process according to the embodiment and the conventional technique will be described. Conventionally, there has been known a technique for generating structural data by processing of extracting information from a combination of attributes and attribute values from non-structural data. For example, as a prior art application example, there has been known a technique of creating size information table data by extracting size information such as height from text data of product description. However, in the above-mentioned conventional technique, since the service providing side determines the size information, it is not always possible to promote the improvement of usability.

The estimation device 100 according to the embodiment, based on the posting information and the attribute information obtained by the obtaining unit, the obtaining unit that obtains the posting information of the user for a predetermined product and the attribute information indicating the attribute of the user, An estimation unit that estimates attribute information of a predetermined product is provided. For example, the estimation device 100 estimates the attribute information of the product based on the attribute information of the user and the posted information indicating what the product was for the user having the attribute information. As described above, the estimation device 100 estimates the attribute information of the product based on the subjectivity of the user with respect to the product, and thus can further improve the usability.

Hereinafter, an example of the estimation process will be described with reference to FIG. FIG. 1 shows an example in which the user U1 posts review information regarding a predetermined product via the terminal device 10. Here, the predetermined product is, for example, a product purchased by the user U1. The terminal device 10 transmits the posted information to the shopping server 200 according to the operation of the user U1 (step S101). At this time, the terminal device 10 may transmit the attribute information of the user U1 to the shopping server 200 together with the posted information. For example, the terminal device 10 may transmit the attribute information of the user U1 stored in the terminal device 10. Further, when the attribute information of the user U1 is registered in the shopping server 200 in advance, the terminal device 10 may transmit only the posted information to the shopping server 200.

Note that FIG. 1 illustrates an example in which the user U2 posts review information regarding a predetermined product via the terminal device 10. As described above, FIG. 1 shows an example in which a plurality of users post review information regarding a predetermined product via the terminal device 10 used by each user.

The shopping server 200 transmits the post information and the attribute information to the estimation device 100 (step S102). Then, the estimation device 100 estimates the attribute information of the predetermined product based on the acquired post information and the attribute information (step S103). For example, the estimation device 100 estimates attribute information of a predetermined product based on post information for the predetermined product when a user who often wears M size clothing purchases the M size of the predetermined product. To do. In this way, the estimation device 100 estimates the attribute information based on the subjectivity of the user included in the posted information. For example, the estimation device 100 estimates the size feeling based on the subjectivity of the user.

For example, when a user who often wears M size clothing posts review information that the M size of a given product is small, the M size of the given product is the M size of another brand (or general It is presumed to be smaller than the standard M size). In this way, the estimation device 100 estimates the size information based on the side of the user who has made a transaction regarding the product, not on the side of the service provider who provides the product, and therefore, the more global (or universal) size information is obtained. Can be estimated. Therefore, the estimation device 100 can promote improvement in usability. In addition, the estimation device 100 can improve the appeal effect of the product information.

An example of using the estimation result by the estimation process will be described below. FIG. 1 shows an example in which the user U3 requests distribution of product information of a predetermined product via the terminal device 10. Here, the predetermined product is, for example, a product which the user U3 is considering purchasing. The terminal device 10 transmits a distribution request for predetermined product information in response to the operation of the user U3 (step S104). At this time, the terminal device 10 may transmit the attribute information of the user U3 to the shopping server 200 together with the distribution request. For example, the terminal device 10 may transmit the attribute information of the user U3 stored in the terminal device 10. Further, when the attribute information of the user U3 is registered in the shopping server 200 in advance, the terminal device 10 may transmit only the distribution request to the shopping server 200.

The shopping server 200 delivers corresponding predetermined product information to the terminal device 10 in response to the delivery request sent from the terminal device 10 (step S105). For example, the shopping server 200 delivers merchandise information having information based on the estimation result of the estimation process. Specifically, the shopping server 200 provides information that the size of each product is one size larger than the size information of a predetermined product determined by the service providing side that provides the product. As a specific example, assuming that a predetermined percentage or more of a plurality of users who usually wear clothes of M size usually post review information that the size of a predetermined product is small, the estimation process is performed. Based on the estimation result by the shopping server 200, the shopping server 200 provides information such as M size of a predetermined product=S size of a general product. In the example of FIG. 1, the shopping server 200 provides information such as “S→M, M→L, L→XL, XL→2XL equivalent when changed to a general size”.

The shopping server 200 may also provide information regarding how the size of each of the predetermined products is felt by the user U3 based on the attribute information of the user U3. Further, the shopping server 200 may provide the size information that best matches the user U3 based on the attribute information of the user U3. For example, the shopping server 200 may estimate the size information suitable for the user U3 based on the review information posted by the user similar to the attribute information of the user U3.

Hereinafter, an example of the product information managed by the shopping server 200 will be described using the example of FIG. 1. The product page C200 illustrated in FIG. 1 is an example of product information. For example, the product page C200 provides product information of a predetermined product. In FIG. 1, the product page C200 includes image information IM1 of a predetermined product, description information IF1 of the predetermined product, cart information CA1 for purchasing the predetermined product, and review information RE1 regarding the predetermined product. included. The information included in the product page C200 shown in FIG. 1 is an example, and the information is not limited to these information.

FIG. 1 shows an example in which the description information IF1 of a predetermined product includes a product name, price, color, size, and material composition. In the explanation information IF1, the product name of the predetermined product is seasonal knit tops, the price of the predetermined product is 2000 yen, the color of the predetermined product is red, and the tradeable size of the predetermined product is S. /M/L/XL, indicating that the material composition of a given product is 30% cotton/70% polyester.

The review information RE1 includes review information regarding a predetermined product from each user. For example, the review information RE1 includes review information RE11 posted by the user U1 and review information RE12 posted by the user U2. The review information RE1 indicates that the user U1 has posted review information regarding a predetermined product such as “I bought an L size, but it was quite relaxed”. Further, the review information RE1 indicates that the user U2 has posted review information regarding a predetermined product, such as "I bought the M size, but it was spicy. I should have bought the L...". In FIG. 1, the case where the review information RE1 includes review information of two users U1 and U2 is shown as an example, but the number of users who post review information is not limited.

The review information RE1 may include user attribute information. As shown in FIG. 1, the review information RE1 may include attribute information AT11 indicating the attribute information of the user U1 and attribute information AT12 indicating the attribute information of the user U2. Further, in FIG. 1, the post information UR11 indicating the post information of the user U1 including the attribute information AT11 of the user U1 and the review information RE11 is set. If the review information RE1 does not include the attribute information AT11 of the user U1, the review information RE11 becomes the post information UR11. Similarly, in FIG. 1, the post information UR12 indicating the post information of the user U2 including the attribute information AT12 and the review information RE12 of the user U2. If the review information RE1 does not include the attribute information AT12 of the user U2, the review information RE12 becomes the post information UR12.

FIG. 1 shows an example in which the attribute information AT11 includes information about height, weight, age, shoulder width, width of the body, and waist. In the attribute information AT11, the height of the user U1 is 164 CM, the weight of the user U1 is 48 KG, the age of the user U1 is 20, the shoulder width of the user U1 is 40 CM, and the width of the user U1 is 48 CM. , West of user U1 is 38 CM. The attribute information AT11 may or may not be displayed on the product page C200. Further, only a part of the information included in the attribute information AT11 may be displayed on the sale item page C200.

In addition, the attribute information AT12 includes information related to items indicating similar user characteristics. In the attribute information AT12, the height of the user U2 is 154 CM, the weight of the user U2 is 40 KG, the age of the user U2 is 30, the shoulder width of the user U2 is 37 CM, and the width of the user U2 is 45 CM. Yes, it indicates that the west of the user U2 is 35 CM. Note that, like the attribute information AT11, the attribute information AT12 may or may not be displayed on the product page C200. Further, only a part of the information included in the attribute information AT12 may be displayed on the sale item page C200.

In addition, in FIG. 1, the case where the estimation device 100 estimates the size information about a predetermined product is illustrated as an example, but the attribute estimated by the estimation device 100 is not limited to the size information, and any information may be used. Good. For example, the estimation device 100 may estimate the type and the degree of spiciness of a given product. In this case, the predetermined product is a dish or food such as mapo tofu.

[2. Configuration of terminal device]
Next, the configuration of the terminal device 10 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the terminal device 10 according to the embodiment. As shown in FIG. 3, the terminal device 10 includes a communication unit 11, an input unit 12, an output unit 13, and a control unit 14.

(Communication unit 11)
The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. Then, the communication unit 11 is connected to a predetermined network N by wire or wirelessly, and transmits and receives information between the estimation device 100 and the shopping server 200 via the predetermined network N.

(Input unit 12)
The input unit 12 receives various operations from the user. For example, the input unit 12 may receive various operations from the user via the display surface by the touch panel function. Further, the input unit 12 may receive various operations from buttons provided on the terminal device 10 or a keyboard or a mouse connected to the terminal device 10.

(Output unit 13)
The output unit 13 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various kinds of information. The output unit 13 also outputs the product information distributed from the shopping server 200.

(Control unit 14)
The control unit 14 is, for example, a controller, and various programs stored in a storage device inside the terminal device 10 are stored in a RAM (Random Access Memory) by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. ) Is executed as a work area. For example, the various programs include programs of applications installed in the terminal device 10. For example, the various programs include an application program that transmits posted information to the shopping server 200 according to a user operation. Further, the control unit 14 is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As illustrated in FIG. 3, the control unit 14 includes a transmitting unit 141, a requesting unit 142, and a receiving unit 143, and realizes or executes the operation of information processing described below.

(Transmission unit 141)
The transmission unit 141 transmits the posted information to the shopping server 200 according to the operation of the user. For example, the transmission unit 141 transmits, to the shopping server 200, posting information for a predetermined product or product information. Specifically, the transmission unit 141 transmits, as post information, review information on a predetermined product that the user has made a transaction with. At this time, the transmission unit 141 may transmit the attribute information of the user to the shopping server 200. For example, the transmission unit 141 may transmit the attribute information of the user stored in the terminal device 10.

(Request unit 142)
The request unit 142 requests the shopping server 200 to deliver predetermined product information according to a user operation. At this time, the request unit 142 may transmit the attribute information of the user to the shopping server 200. For example, the request unit 142 may transmit the user attribute information stored in the terminal device 10.

(Reception unit 143)
The receiving unit 143 receives the predetermined product information distributed from the shopping server 200 in response to the request from the requesting unit 142. The receiving unit 143 also receives product information including information based on the estimation result estimated by the estimation device 100. Here, the information based on the estimation result is, for example, attribute information of a predetermined product. For example, the receiving unit 143 receives the product information including the changed size information based on the estimation result by the estimation device 100. The receiving unit 143 may also receive the product information including the information selected based on the estimation result by the estimation device 100. For example, the receiving unit 143 may receive, based on the changed size information and the attribute information, the product information including the size information that is selected as the best match for the other user who requested the distribution.

[3. Configuration of estimation device]
Next, the configuration of the estimation device 100 according to the embodiment will be described with reference to FIG. FIG. 4 is a diagram illustrating a configuration example of the estimation device 100 according to the embodiment. As shown in FIG. 4, the estimation device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The estimation apparatus 100 has an input unit (for example, a keyboard or a mouse) that receives various operations from the administrator of the estimation apparatus 100, and a display unit (for example, a liquid crystal display) for displaying various information. Good.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC. Then, the communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information between the terminal device 10 and the shopping server 200 via the network N.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 4, the storage unit 120 includes a posted information storage unit 121, a user information storage unit 122, and an estimated information storage unit 123.

The posted information storage unit 121 stores the posted information transmitted from the terminal device 10. Specifically, the posted information storage unit 121 stores posted information posted for a predetermined product or product information. Here, FIG. 5 illustrates an example of the posted information storage unit 121 according to the embodiment. As shown in FIG. 5, the post information storage unit 121 has items such as “post ID”, “user ID”, “product”, “post information”, and “post date/time”.

The “post ID” indicates identification information for identifying the acquired post information. The “user ID” indicates identification information for identifying the user who posted the posted information identified by the “posted ID”. “Product” indicates a product that is the target of the posted information. In the example shown in FIG. 5, an example is shown in which conceptual information such as “product #1” is stored in “product”, but product information is actually stored. "Posted information" indicates posted information posted by the corresponding user. “Posted date and time” indicates the date and time when posted information was posted.

The posted information storage unit 121 may have an item such as “attribute information”. The “attribute information” indicates the attribute information of the user. The “attribute information” indicates the attribute information of the user corresponding to the “user ID”, for example. The "attribute information" may store conceptual information such as "attribute information #1", or may store actual attribute information.

The user information storage unit 122 stores user attribute information. For example, the user information storage unit 122 stores the attribute information transmitted from the terminal device 10. For example, the user information storage unit 122 may store the attribute information transmitted from the external server. Further, the user information storage unit 122 may store the attribute information transmitted when posting the posting information. Further, the user information storage unit 122 may store the attribute information transmitted when the distribution of the product information is requested. Here, FIG. 6 illustrates an example of the user information storage unit 122 according to the embodiment. As shown in FIG. 6, the user information storage unit 122 has items such as “user ID”, “height”, “weight”, “shoulder width”, and “width of body”.

The “user ID” indicates identification information for identifying the user. The “user ID” indicates identification information for identifying the user who posted the posted information. The "user ID" indicates identification information for identifying another user who has made a distribution request. “Height” indicates the height of the user as attribute information. “Weight” indicates the weight of the user as attribute information. “Shoulder width” indicates the shoulder width of the user as attribute information. The “width of the body” indicates the width of the body of the user as attribute information. Further, the user information storage unit 122 may have items such as “attribute information” instead of items such as “height”, “weight”, “shoulder width”, and “width of body”. In this case, the “attribute information” may collectively indicate information about the height, weight, shoulder width, and width of the user.

The estimation information storage unit 123 stores the estimation result estimated by the estimation device 100. The estimated information storage unit 123 stores the attribute information of the predetermined product estimated by the estimation device 100. Here, FIG. 7 illustrates an example of the estimated information storage unit 123 according to the embodiment. As shown in FIG. 7, the estimated information storage unit 123 has items such as “estimated ID”, “product”, “product ID”, and “product attribute”.

The “estimation ID” indicates identification information for identifying the estimation result estimated by the estimation device 100. “Product” indicates a product whose attribute information is estimated by the estimation device 100. In the example shown in FIG. 7, an example is shown in which conceptual information such as “product #1” is stored in “product”, but product information is actually stored. “Product ID” indicates identification information for identifying a product whose attribute information is estimated by the estimation device 100. “Product attribute” indicates attribute information of a predetermined product. In the “product attribute”, for example, size information estimated based on the subjectivity of the user is stored. The example shown in FIG. 7 shows an example in which conceptual information such as “product attribute #1” is stored in “product attribute”, but in reality, attribute information of a predetermined product such as size information is stored. To be done.

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

As illustrated in FIG. 4, the control unit 130 includes an acquisition unit 131, an extraction unit 132, an estimation unit 133, a determination unit 134, and a transmission unit 135, and realizes the operation of information processing described below. Or run. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 4, and may be another configuration as long as it is a configuration for performing information processing described later.

(Acquisition unit 131)
The acquisition unit 131 acquires the information transmitted from the shopping server 200. Specifically, the acquisition unit 131 acquires post information of the user on a predetermined product and attribute information of the user who posted the post information. For example, the acquisition unit 131 acquires post information for a predetermined product traded in the online shopping mall. Further, the acquisition unit 131 acquires review information for a predetermined product as the posting information. In addition, the acquisition unit 131 may acquire review information for predetermined product information as the posting information. Further, the acquisition unit 131 acquires, as the attribute information, size information regarding the body type of the user who posted the posted information. The acquisition unit 131 acquires the post information of a plurality of users for a predetermined product and the attribute information of the plurality of users in association with each other.

The acquisition unit 131 may acquire attribute information of another user who has requested distribution of predetermined product information. For example, the acquisition unit 131 may acquire, as the attribute information, size information regarding the body type of another user who has requested distribution.

(Extractor 132)
The extraction unit 132 extracts specific information from the posted information acquired by the acquisition unit 131. For example, the extraction unit 132 extracts specific information regarding a predetermined product. For example, the extraction unit 132 extracts specific information based on the result of the semantic analysis of the input information (posted information) of the user by appropriately using the conventional techniques of various natural language processing techniques of morphological analysis. Specifically, the extraction unit 132 extracts, from the posted information acquired by the acquisition unit 131, information regarding the size feeling that the user feels about the predetermined product. Further, specifically, the extraction unit 132 may extract, from the posted information acquired by the acquisition unit 131, information on a predetermined taste sensed by the user regarding a predetermined product. For example, the extraction unit 132 may extract information regarding the degree of hotness felt by the user as the information regarding the predetermined taste.

(Estimation unit 133)
The estimating unit 133 estimates the attribute information of a predetermined product based on the post information and the attribute information acquired by the acquiring unit 131. For example, the estimation unit 133 may perform estimation based on the acquired plurality of pieces of post information and the corresponding pieces of attribute information. For example, the estimation unit 133 may estimate the attribute information by calculating the correlation between the posted information and the attribute information based on the plurality of combinations of the acquired posted information and the attribute information. In addition, the estimation unit 133 may estimate the attribute information by calculating the correlation between the posted information and the attribute information when the number of acquired combinations of the posted information and the attribute information is equal to or larger than a predetermined threshold. ..

The estimation unit 133 estimates, for example, clothing size information or cooking flavor information as attribute information of a predetermined product. Specifically, the estimation unit 133 determines that the predetermined product is based on the posted information about the size feeling acquired by the acquisition unit 131 (or extracted by the extraction unit 132) and the attribute information about the size of the user. Estimate the size information you have. In addition, specifically, the estimation unit 133 includes information on a predetermined taste acquired by the acquisition unit 131 (or extracted by the extraction unit 132) and attribute information indicating the specialty of the user on a predetermined taste. Based on, the flavor information of a given product is estimated. More specifically, the estimation unit 133 determines, based on the information regarding the degree of spiciness of a predetermined product and the attribute information indicating the resistance of the user to the taste, as the information regarding the predetermined taste. Information about the degree of hotness of the product may be estimated.

Here, the attribute information indicating the resistance of the hotness to the taste is, for example, the sex or age of the user. For example, the estimation unit 133 evaluates that a user who has attribute information such as a man in his 20s is more resistant to the taste of spiciness than a user who has attribute information such as a woman in his 40s, and the degree of spiciness is related to this. The information may be estimated. The attribute information indicating the resistance of the hot taste to the taste is, for example, the ethnicity of the user. For example, the estimation unit 133 estimates that a user born in an area that prefers to eat spicy food on a daily basis is more resistant to the taste of spiciness than a user born in an area that does not. May be. In this way, the estimation unit 133 may estimate the information regarding the degree of hotness of a predetermined product based on the attribute information including the ethnic information indicating the ethnicity of the user.

The estimation unit 133 may estimate index information indicating the degree of attribute information of a predetermined product. For example, the estimation unit 133, as the index information indicating the degree in the size information, the size S is a size for a user of “height 150 CM to 155 CM, shoulder width 36 CM to 38 CM”, and the M size is “height 155 CM to 160 CM. It may be estimated that the index information is a size intended for a user having a shoulder width of 38 CM to 40 CM and the L size is a size intended for a user having a height of 160 CM to 165 CM and a shoulder width of 40 CM to 42 CM. .. Further, for example, the estimation unit 133 may estimate index information indicating the degree of the degree of hotness being “level 2 in 5 levels” as the index information indicating the degree of information on the degree of hotness.

(Determination unit 134)
The determination unit 134 determines the matching degree of the other user with the attribute information of the predetermined product, based on the attribute information estimated by the estimation unit 133 and the attribute information of the other user acquired by the acquisition unit 131. To do. The determination unit 134 determines the degree of matching with the other user who has requested the distribution, based on the attribute information of the other user who requested the distribution of the predetermined product information. For example, when the attribute information estimated by the estimation unit 133 is size information, the determination unit 134 determines a predetermined value based on the estimated size information and the attribute information of another user who has requested distribution. The matching degree of another user with respect to the specific size of the item is determined. Specifically, the determination unit 134 determines whether or not the S size of a predetermined product is appropriate for another user who has made a distribution request. Further, the determination unit 134 may determine which of the S/M/L sizes is suitable for the other user who has made the distribution request.

For example, when the attribute information estimated by the estimation unit 133 is information regarding the degree of hotness, the determination unit 134 includes information regarding the estimated degree of hotness and other users who have requested distribution. Based on the attribute information, how hard other users feel about the spiciness of a predetermined product is determined. That is, the determination unit 134 determines whether or not the degree of difficulty of the predetermined product is appropriate for the other user who has requested the distribution. In addition, the determination unit 134 may determine which level of difficulty the user feels to be difficult for other users who have requested distribution.

(Transmission unit 135)
The transmission unit 135 transmits the estimation result of the estimation unit 133 to the shopping server 200. For example, the transmission unit 135 transmits the attribute information of a predetermined product. For example, the transmission unit 135 transmits index information indicating the degree of attribute information of a predetermined product. Further, the transmission unit 135 causes the shopping server to transmit the determination result of the determination unit 134 to 200. For example, the transmission unit 135 transmits information about the matching degree based on the attribute information of another user with respect to the estimation result by the estimation unit 133.

[4. Shopping server configuration]
Next, the configuration of the shopping server 200 according to the embodiment will be described with reference to FIG. FIG. 8 is a diagram showing a configuration example of the shopping server 200 according to the embodiment. As shown in FIG. 8, the shopping server 200 includes a communication unit 210, a storage unit 220, and a control unit 230. The shopping server 200 has an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator of the shopping server 200, and a display unit (for example, a liquid crystal display) for displaying various information. Good.

(Communication unit 210)
The communication unit 210 is realized by, for example, a NIC. Then, the communication unit 210 is connected to the network N by wire or wirelessly, and transmits/receives information between the terminal device 10 and the estimation device 100 via the network N.

(Storage unit 220)
The storage unit 220 is realized by, for example, a semiconductor memory device such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 8, the storage unit 220 includes a product information storage unit 221, a posted information storage unit 222, and a user information storage unit 223.

The product information storage unit 221 stores product information regarding products traded in a predetermined online shopping mall. For example, the product information storage unit 221 stores product information that can be distributed to the terminal device 10. The product information storage unit 221 stores information included in, for example, a predetermined product page. The product information storage unit 221 stores, for example, image information of a predetermined product, description information (for example, product name, price, etc.), cart information, and the like in association with each product.

Further, the product information storage unit 221 may store posting information posted by the user for a predetermined product or product information via the terminal device 10. For example, the product information storage unit 221 may store the review information transmitted from the terminal device 10. In this case, the product information storage unit 221 may store image information and description information of a predetermined product, and information such as posted information posted by the user for the predetermined product in association with each product. Further, the product information storage unit 221 may store attribute information of the user who has posted. In this case, the product information storage unit 221 stores information such as image information and description information of a predetermined product, review information of each user with respect to the predetermined product, and attribute information of the user who posted the product in association with each product. You may.

The posted information storage unit 222 stores the same information as the posted information storage unit 121 shown in FIG. Specifically, the posted information storage unit 222 stores the posted information posted by the user for a predetermined product or product information via the terminal device 10. For example, the posted information storage unit 222 stores the review information transmitted from the terminal device 10 for each user posting. For example, the posted information storage unit 222 stores review information and attribute information in association with each user's posting.

The user information storage unit 223 stores the same information as the user information storage unit 122 shown in FIG. The user information storage unit 223 stores attribute information of the user who posted. For example, the user information storage unit 223 stores, as attribute information, information such as the height, weight, age, and shoulder width of the user. In addition, the user information storage unit 223 may store the attribute information transmitted from the terminal device 10 or may store the attribute information registered in a predetermined online shopping mall.

(Control unit 230)
The control unit 230 is a controller, and is realized by, for example, a CPU, an MPU, or the like executing various programs stored in a storage device inside the shopping server 200 using a RAM as a work area. The control unit 230 is a controller and is realized by an integrated circuit such as an ASIC or FPGA.

As illustrated in FIG. 8, the control unit 230 includes an acquisition unit 231, a transmission unit 232, a reception unit 233, and a distribution unit 234, and realizes or executes the operation of information processing described below. The internal configuration of the control unit 230 is not limited to the configuration shown in FIG. 8, and may be another configuration as long as it is a configuration for performing information processing described later.

(Acquisition unit 231)
The acquisition unit 231 acquires the posted information transmitted from the terminal device 10. For example, the acquisition unit 231 acquires post information posted by a user for a predetermined product or product information. The acquisition unit 231 may also acquire attribute information of the user who posted. For example, the acquisition unit 231 may acquire the user attribute information transmitted from the terminal device 10.

The acquisition unit 231 acquires the distribution request transmitted from the terminal device 10. For example, the acquisition unit 231 acquires a distribution request for predetermined product information. At this time, the acquisition unit 231 may acquire attribute information of another user who has made a distribution request. The acquisition unit 231 may also acquire the attribute information of another user stored in the storage unit 220.

(Transmission unit 232)
The transmission unit 232 transmits the information acquired by the acquisition unit 231 to the estimation device 100. For example, the transmission unit 232 transmits the post information acquired by the acquisition unit 231. For example, the transmission unit 232 transmits the attribute information acquired by the acquisition unit 231. For example, the transmission unit 232 transmits the post information and the attribute information acquired by the acquisition unit 231.

(Reception unit 233)
The receiving unit 233 receives information about the estimation result estimated by the estimation device 100. The receiving unit 233 receives information about the estimation result of the attribute information of a predetermined product.

(Distributor 234)
The distribution unit 234 distributes the corresponding product information to the terminal device 10 in response to the distribution request acquired by the acquisition unit 231. Further, the distribution unit 234 distributes the information regarding the estimation result received by the reception unit 233 to the terminal device 10.

[5. Estimation process flow)
Next, the procedure of the estimation process by the estimation system 1 according to the embodiment will be described with reference to FIGS. 9 to 10. 9 to 10 are flowcharts showing the procedure of the estimation process by the estimation system 1 according to the embodiment.

As shown in FIG. 9, the estimation device 100 acquires the user's post information and attribute information for a predetermined product (step S201). The estimation apparatus 100 extracts the specific information felt by the user for the predetermined product from the acquired posting information (step S202). The estimation device 100 estimates the attribute information of a predetermined product based on the extracted specific information and attribute information (step S203).

In addition, as illustrated in FIG. 10, the estimation device 100 acquires post information and attribute information of a plurality of users for a predetermined product (step S301). The estimation device 100 determines whether the number of acquired information satisfies a predetermined condition (step S302). When the number of acquired information does not satisfy the predetermined condition (step S302; NO), the estimation device 100 waits until the predetermined condition is satisfied. In addition, when the number of acquired information satisfies the predetermined condition (step S302; YES), the estimation device 100 calculates the correlation between the acquired posted information and the attribute information (step S303). Further, the estimation device 100 estimates the attribute information of the predetermined product based on the calculated correlation (step S304).

[6. effect〕
As described above, the estimation device 100 according to the embodiment has the acquisition unit 131 and the estimation unit 133. The acquisition unit 131 acquires post information of a user for a predetermined transaction target and attribute information indicating the attribute of the user. The estimation unit 133 estimates the attribute of a predetermined transaction target based on the post information and the attribute information acquired by the acquisition unit 131.

As a result, the estimation device 100 according to the embodiment makes an estimation based on the information on the user side, not on the service providing side, and thus can further improve usability.

The estimation unit 133 also estimates an index indicating the degree of the attribute.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

In addition, the acquisition unit 131 acquires post information of a plurality of users for a predetermined transaction target and attribute information of a plurality of users in association with each other. In addition, the estimation unit 133 estimates the attribute of a predetermined transaction target based on the plurality of combinations of the post information and the attribute information acquired by the acquisition unit 131.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

In addition, the estimation device 100 according to the embodiment includes the extraction unit 132 that extracts, from the posted information acquired by the acquisition unit 131, information regarding the size feeling felt by the user regarding a predetermined transaction target. In addition, the estimation unit 133 estimates the size information of a predetermined transaction target based on the information about the size feeling extracted by the extraction unit 132 and the attribute information about the size of the user.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

The acquisition unit 131 also acquires attribute information of another user who has requested distribution of information regarding a predetermined transaction target. In addition, the estimation device 100 according to the embodiment, based on the size information estimated by the estimation unit 133 and the attribute information of other users acquired by the acquisition unit 131, with respect to a specific size of a predetermined transaction target. It has a determination unit 134 that determines the size feeling of other users.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

In addition, the estimation device 100 according to the embodiment includes the extraction unit 132 that extracts, from the posted information acquired by the acquisition unit 131, information regarding a predetermined taste sensed by the user regarding a predetermined transaction target. In addition, the estimation unit 133 estimates the flavor information of a predetermined transaction target based on the information on the predetermined taste extracted by the extraction unit 132 and the attribute information indicating the specialty of the user on the predetermined taste. ..

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

In addition, the extraction unit 132 extracts, from the posted information acquired by the acquisition unit 131, information regarding the degree of pain that the user feels regarding a predetermined transaction target. In addition, the estimation unit 133, based on the information on the degree of hotness extracted by the extraction unit 132 and the attribute information indicating the resistance of the hotness of the user to the taste, determines the hotness of the predetermined transaction target. Estimate information about degree.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

Further, the estimation unit 133 estimates information regarding the degree of pain of a predetermined transaction target based on attribute information including ethnic information indicating the ethnicity of the user.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

Further, the acquisition unit 131 acquires, as a predetermined transaction target, post information for a predetermined product that is traded in the online shopping mall. Further, the estimation unit 133 estimates the attribute of a predetermined product.

Thereby, the estimation device 100 according to the embodiment can further promote improvement in usability.

[7. Hardware configuration]
In addition, the terminal device 10, the estimation device 100, and the shopping server 200 according to the above-described embodiments are realized by, for example, a computer 1000 having a configuration illustrated in FIG. 11. FIG. 11 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the terminal device 10, the estimation device 100, and the shopping server 200. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I/F) 1500, an input/output interface (I/F) 1600, and a media interface (I/F) 1700.

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

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. The communication interface 1500 receives data from another device via a predetermined communication network, sends the data to the CPU 1100, and transmits the data generated by the CPU 1100 to another device via the predetermined communication network.

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

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

For example, when the computer 1000 functions as the terminal device 10, the estimation device 100, and the shopping server 200 according to the embodiment, the CPU 1100 of the computer 1000 executes the programs loaded on the RAM 1200 to cause the control units 14, 130 and The function of 230 is realized. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via a predetermined communication network.

[8. Other]
Further, of the processes described in the above embodiment, all or part of the processes described as being automatically performed may be manually performed, or the processes described as manually performed may be performed. All or part of the process can be automatically performed by a known method. In addition, the processing procedures, specific names, information including various data and parameters shown in the above-mentioned documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Further, each component of each device shown in the drawings is functionally conceptual and does not necessarily have to be physically configured as shown. That is, the specific form of distribution/integration of each device is not limited to that shown in the figure, and all or part of the device may be functionally or physically distributed/arranged in arbitrary units according to various loads and usage conditions. It can be integrated and configured.

In addition, the above-described embodiments can be appropriately combined within the range in which the processing content is not inconsistent.

As described above, some of the embodiments of the present application have been described in detail based on the drawings, but these are examples, and various modifications based on the knowledge of those skilled in the art, including the modes described in the section of the disclosure of the invention, It is possible to implement the present invention in other forms with improvements.

Further, the "section (module, unit)" described above can be read as "means" or "circuit". For example, the acquisition unit can be read as an acquisition unit or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 estimation system 10 terminal device 11 communication part 12 input part 13 output part 14 control part 100 estimation device 110 communication part 120 storage part 121 posted information storage part 122 user information storage part 123 estimated information storage part 130 control part 131 acquisition part 132 extraction Part 133 Estimating part 134 Judgment part 135 Sending part 141 Sending part 142 Requesting part 143 Receiving part 200 Shopping server 210 Communication part 220 Storage part 221 Product information storage part 222 Posting information storage part 223 User information storage part 230 Control part 231 Acquisition part 232 Transmission unit 233 Reception unit 234 Distribution unit

Claims (11)

An acquisition unit that acquires user's posted information for a predetermined transaction target and attribute information indicating the attribute of the user,
An estimation unit that estimates an attribute of the predetermined transaction target based on the post information and the attribute information acquired by the acquisition unit,
An estimation device comprising: The estimation unit is
The estimation device according to claim 1, wherein an index indicating a degree of the attribute is estimated. The acquisition unit is
Acquired by correlating post information of a plurality of users with respect to a predetermined transaction target and attribute information of the plurality of users,
The estimation unit is
The estimation device according to claim 1 or 2, wherein the attribute of the predetermined transaction target is estimated based on a plurality of combinations of the post information and the attribute information acquired by the acquisition unit. Further comprising an extraction unit that extracts information regarding the size feeling felt by the user with respect to the predetermined transaction target from the posting information acquired by the acquisition unit,
The estimation unit is
The size information held by the predetermined transaction target is estimated based on the size information extracted by the extraction unit and the attribute information related to the size of the user. The estimation device according to claim 1. The acquisition unit is
Obtaining attribute information of other users who have requested distribution of information regarding the predetermined transaction target,
Based on the size information estimated by the estimation unit and the attribute information of the other user acquired by the acquisition unit, the size feeling of the other user with respect to the specific size of the predetermined transaction target is determined. Determination unit to
The estimation device according to claim 4, further comprising: An extraction unit that extracts information regarding a predetermined taste sensed by the user with respect to the predetermined transaction target from among the posted information acquired by the acquisition unit,
The estimation unit is
The flavor information of the predetermined transaction target is estimated based on the information about the predetermined taste extracted by the extraction unit and the attribute information indicating the specialty of the user about the predetermined taste. The estimation device according to claim 1. The extraction unit is
From the posted information acquired by the acquisition unit, the information regarding the degree of pain felt by the user regarding the predetermined transaction target is extracted,
The estimation unit is
Based on the information about the degree of hotness extracted by the extraction unit and the attribute information indicating the resistance of the user to the taste of hotness, the information about the degree of hotness of the predetermined transaction target is estimated. The estimation device according to claim 6, wherein The estimation unit is
The estimation apparatus according to claim 7, wherein the estimation device estimates information regarding the degree of pain of the predetermined transaction target based on attribute information including ethnic information indicating the ethnicity of the user. The acquisition unit is
As the predetermined transaction target, obtain post information for a predetermined product traded in the online shopping mall,
The estimation unit is
The estimation device according to claim 1, wherein an attribute of the predetermined product is estimated. A computer implemented estimation method comprising:
An acquisition step of acquiring user's posted information for a predetermined transaction target and attribute information indicating the attribute of the user,
An estimating step of estimating an attribute of the predetermined transaction target based on the post information and the attribute information obtained in the obtaining step;
An estimation method characterized by including. An acquisition procedure for acquiring user's posted information for a predetermined transaction target and attribute information indicating the attribute of the user,
An estimation procedure for estimating an attribute of the predetermined transaction target based on the post information and the attribute information acquired by the acquisition procedure,
An estimation program that causes a computer to execute.

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