JP2021093216A - Recommendation information specification device, recommendation information specification system, recommendation information specification method, terminal device, and program - Google Patents

Abstract

To provide a recommendation information specification device, a recommendation information specification system, a recommendation information specification method, and a program that can specify recommendation information including commodity information that matches real-time preference of a user who is shopping in a shop.SOLUTION: In a server device 11, a recipe selection processing unit 315 selects and acquires a cooking recipe using high-ranking commodities from a cooking recipe database 17. A necessary commodity determination unit 316 compares commodities used for the selected cooking recipe with the high-ranking commodities, and determines necessary commodities that are necessary for a dish indicated by the selected cooking recipe. If there are necessary commodities, the server device specifies the necessary commodities as recommended commodities and transmits the selected cooking recipe to a user terminal 15 together with the recommended commodities.SELECTED DRAWING: Figure 6

Description

The present invention relates to a recommended information specifying device for specifying recommended information suitable for the taste of a user who uses a store, a recommended information specifying system, a recommended information specifying method, and a program.

In electronic commerce and advertisements on the Internet, there is known a method of extracting so-called recommended information according to a user's taste from a huge amount of information and displaying it on a terminal device used by the user. The recommended information is also referred to as recommendation information, and corresponds to, for example, product information including recommended products that should be recommended that may match the taste of the user. The recommended information is specified based on behavior history such as history information of a user purchasing a product on a WEB site (product purchase history) and history information of browsing a product introduction page (product browsing history). .. The function of analyzing the behavior history, identifying and presenting the recommended information according to the user's preference based on a predetermined algorithm is called a recommendation function, and has been widely used in recent years.

Conventionally, a recommendation device having the recommendation function has been proposed (see Patent Document 1). The recommendation device displays recommended information according to the taste of a customer (visitor) on a tablet or the like used by an employee in a store such as a retail store.

Further, in recent years, a payment system using an information code such as a bar code or a QR code (registered trademark) indicating the content or price of a product has been proposed (see Patent Document 2). A mobile terminal (for example, a smartphone) of a customer who uses a store is equipped with a code reading function for reading an information code given to a product. According to the payment system, the customer uses a mobile terminal to read the information code attached to the product package or the like, puts the product in the shopping cart, and then charges the product amount included in the read information code. Make a payment. Payment of the product amount can be made, for example, by using a cash register that can communicate with the mobile terminal, payment by electronic money registered in the mobile terminal, online credit payment, or the like.

Further, conventionally, there is known a shopping support device that searches for a cooking recipe using a user's product purchase history and presents it to the user (see Patent Document 3). The shopping support device displays a list of ingredients recently purchased by the user and a list of ingredients that attracted attention at the store on the terminal device used by the user, and the user selects the ingredients to be used from the list. Then, these ingredients to be used are compared with the ingredients of the cooking in the database in which the cooking recipes are accumulated, and the cooking recipe suitable for the ingredients to be used is searched and presented to the user.

Japanese Unexamined Patent Publication No. 2017-215667 Japanese Unexamined Patent Publication No. 2015-185089 Japanese Unexamined Patent Publication No. 2014-49039

However, since the conventional recommendation function identifies recommended information that suits the user's taste from the past product purchase history and product browsing history, for example, while shopping at a store such as a retail store ( It is difficult to present recommended information that takes into account the current tastes and wishes of users (who are shopping around). Further, in the conventional shopping support device, it is not possible to provide a cooking recipe suitable for the user's current tastes and wishes unless the user selects the ingredients and obtains the information.

An object of the present invention is a recommended information identification device, a recommended information identification system, a recommended information identification method, which can specify recommended information including product information matching the real-time taste of a user who is shopping at a store. And to provide the program.

The recommended information specifying device according to one aspect of the present invention includes a purchase target information acquisition unit that acquires purchase target information regarding each product selected as a purchase target of the user at the store from a terminal device used by the user at the store. , Recommended information for identifying recommended information according to the user from a plurality of product information related to a plurality of products provided at the store based on the ranking information regarding the selection order of the selected products and the purchase target information. It has a specific part.

In addition, the recommended information identification system according to another aspect of the present invention acquires purchase target information for each product selected as a purchase target of the user at the store from a terminal device used by the user at the store. Based on the department, the ranking information regarding the selection order of the selected products, and the purchase target information, the recommended information according to the user is specified from the plurality of product information regarding the plurality of products provided at the store. It includes a recommended information specifying unit and a recommended information output unit that outputs the recommended information specified by the recommended information specifying unit to the terminal device.

Further, the recommended information identification method according to another aspect of the present invention is to acquire purchase target information for each product selected as a purchase target of the user at the store from a terminal device used by the user at the store. Based on the step, the purchase target information, and the ranking information regarding the selection order of the selected products, the recommended information according to the user is specified from the plurality of product information regarding the plurality of products provided at the store. It includes recommended information identification steps.

The present invention can also be regarded as a program for causing a computer to execute each step of the recommended information identification method, or as a computer-readable recording medium in which such a program is recorded non-temporarily.

According to the present invention, it is possible to specify recommended information including product information that matches the real-time taste of a user who is shopping at a store. By presenting such recommended information to the user, the user can quickly obtain product information that matches his / her current taste.

Further, according to the present invention, by further providing a recipe acquisition unit and a deficient product determination unit, information on deficient products related to deficient products in a cooking recipe can be extracted from a plurality of product information, and the recipe acquisition unit The acquired cooking recipe and the missing product information can be specified as the recommended information. By presenting such recommended information to the user, the user can obtain a cooking recipe that matches his / her taste at the present time, and can easily decide the menu that could not be decided. In addition, it is possible to obtain product information that is lacking in the cooking recipe, and it is possible to prevent forgetting to buy products such as ingredients, seasonings, and kitchen items necessary for the decided menu. In addition, the store side (seller) can promote sales of the shortage product, and thus can increase the purchase rate of the product.

FIG. 1 is a diagram showing a configuration of an information processing system according to an embodiment of the present invention. FIG. 2 is a diagram showing an example of a screen displayed on a mobile terminal constituting an information processing system. FIG. 3 is a block diagram showing the configuration of each device constituting the information processing system. FIG. 4 is a block diagram showing a configuration of a ranking determination unit of a server device constituting an information processing system. FIG. 5 is a diagram showing the order of each product handled by the store. FIG. 6 is a flowchart showing a first processing example of the recommendation processing executed in the information processing system. FIG. 7 is a flowchart showing a second processing example of the recommendation processing executed in the information processing system. FIG. 8 is a flowchart showing a third processing example of the recommendation processing executed in the information processing system. FIG. 9 is a flowchart showing a fourth processing example of the recommendation processing executed in the information processing system. FIG. 10 is a flowchart showing an example of a learning operation executed in the learning unit of the information processing system.

Hereinafter, embodiments of the present invention will be described with reference to the drawings as appropriate. It should be noted that the embodiments described below are merely examples that embody the present invention, and do not limit the technical scope of the present invention.

[Information processing system 100]
As shown in FIG. 1, the information processing system 100 (recommended information specifying system of the present invention) according to the embodiment of the present invention includes a server device 11 (an example of the recommended information specifying device of the present invention) and a gate device for entering a store. 12, Gate device 13 for leaving the store, self-type register 14, user terminal 15 (an example of the terminal device of the present invention), employee terminal 16 used by employees of the store 200, and used for cooking. Includes a cooking recipe database 17 (an example of a cooking recipe storage unit of the present invention) that stores product information and cooking recipes in association with each other. The gate device 12, the gate device 13, and the register 14 may all be one or may be plural. In the present embodiment, for example, an example in which the information processing system 100 is introduced into a store 200 such as a supermarket that handles a wide variety of products will be described. Of course, the store 200 in which the information processing system 100 is introduced is not limited to a supermarket, and may be an actual retail store that handles a plurality of products, or may be a virtual store on the Internet.

The gate device 12 is installed near the entrance of the store 200, and the gate device 13 is installed near the exit of the store 200. The user terminal 15 is a terminal device possessed and used by a user (user) who has entered the store 200 when purchasing a product displayed in the store 200 in the store 200, and is, for example, a smartphone or a smartphone. It is a mobile terminal such as a mobile phone or a tablet terminal. The employee terminal 16 is a terminal device used by employees of the store 200, and is, for example, a mobile terminal such as a laptop computer, a smartphone, or a tablet terminal.

Hereinafter, with reference to FIGS. 1 and 2, a series of flow from the user visiting the store 200 to purchasing the product and leaving the store will be illustrated.

First, a user who visits the store 200 approaches the gate device 12 for entering the store from the entrance while possessing the user terminal 15. When the user approaches the gate device 12, the user terminal 15 communicates with the gate device 12 by short-range wireless communication represented by Bluetooth, FeliCa (registered trademark), or the like. At this time, the user identification information (ID number, name, gender, age, etc.) stored in the user terminal 15 is transmitted to the gate device 12. The user identification information is information for identifying a user of the store 200. The user identification information is transferred from the gate device 12 to the server device 11 through a communication network N1 such as a wireless LAN (in-store LAN) installed in the store 200. As a result, the server device 11 recognizes that a user registered in advance has visited the store. If the user terminal 15 includes the purchase history information of the user in the store 200, the purchase history information is also transmitted to the gate device 12 and transferred to the server device 11 through the communication network N1. .. Here, the purchase history information is history information of products that the user has purchased in the past at the store 200.

A shopping application used in a system for shopping while scanning an information code (bar code, QR code, etc.) attached to a product is pre-installed on the user terminal 15. When the user terminal 15 communicates with the gate device 12, the user terminal 15 automatically activates the shopping application. At this time, for example, the screen shown in FIG. 2A is displayed on the operation display unit 22 (see FIG. 3) of the user terminal 15. As a result, the user can purchase the product in the store 200 by using the shopping application.

While buying around the store 200, the user picks up the product he / she wants to purchase (the product to be purchased) from the display shelf, and obtains the information code attached to the product from the imaging unit 24 of the user terminal 15. Image (scan) by (see FIG. 3). The shopping application of the user terminal 15 reads the price information (information including the product name, amount of money, and product ID) of the product included in the information code, and operates the operation display unit 22 of the user terminal 15 (see FIG. 3). ). For example, when the user scans three items a, b, c, the user terminal 15 includes the price information of the three items a, b, c selected as purchase targets in FIG. 2 ( The screen shown in B) is displayed. The read price information is stored in the user terminal 15, is transmitted from the user terminal 15 to the server device 11 through the communication network N1, and is also stored in the server device 11.

When excluding the product selected as the purchase target from the purchase target, that is, canceling the purchase schedule, the user selects the product to be canceled from the screen shown in FIG. 2 (B), and further selects "Cancel". .. As a result, the price information of the product for which the purchase of the product is desired to be canceled is deleted from the screen, and the cancellation information indicating that the product has been canceled is transmitted from the user terminal 15 to the server device 11 through the communication network N1.

The server device 11 reads the purchase history information (an example of the action history of the present invention) corresponding to the user identification information transferred from the gate device 12 from the storage unit 32 (customer information storage unit 321), and will be described later. The recommendation process (see FIG. 7) is executed. In this recommendation process, recommendation information (an example of the recommended information of the present invention) according to the user is obtained from a plurality of product information related to all the products (products that can be sold at the store 200) managed in the server device 11. It is a process to identify. Specifically, product information that will match the taste of the user is extracted based on a predetermined algorithm, and the extracted product information is specified as the recommendation information. Then, the specified recommendation information is transmitted to the user terminal 15 through the communication network N1. In the user terminal 15, the recommendation information is displayed in a pop-up format or the like on the operation display unit 22 (see FIG. 3) of the user terminal 15 so that the user who is buying around can easily notice it.

When paying for the read product (settlement), the user goes to the register 14 and "pays" (Fig. 2 (B)) with the user terminal 15 held in the communication unit provided in the register 14. ) Refer to). As a result, the user terminal 15 communicates with the register 14 through the short-range radio, and the user identification information is transmitted from the user terminal 15 to the register 14. Further, the user identification information transmitted to the register 14 is transferred from the register 14 to the server device 11 through the communication network N1. After that, the server device 11 extracts the price information of the payment target corresponding to the user identification information and transfers it to the register 14. Then, in the register 14, the settlement process of the amount indicated by the price information is executed based on the settlement method designated by the user. When the payment process is completed, the user terminal 15 displays a screen indicating that the payment has been completed.

Note that the settlement process may be performed online between the user terminal 15 and the server device 11 without using the register 14. The settlement process is performed as follows. For example, when the user selects "payment" on the screen of FIG. 2B, the payment process is started. For example, the user terminal 15 transmits the price information of the products a, b, and c to be settled to the server device 11 together with the user identification information. The server device 11 transmits a payment request to a payment server (not shown) connected via the Internet based on the price information. The payment server executes payment processing by a payment system according to the payment business operator. After that, the execution of the payment process is transmitted to the user terminal 15 via the server device 11, and a message to that effect is displayed on the operation display unit 22 (see FIG. 3).

When the payment process is completed, the register 14 transmits information on the purchased product for which payment has been completed to the server device 11. The server device 11 updates the inventory quantity of the product managed by the server device 11 based on the information received from the register 14. Further, the server device 11 updates the purchase history information stored and managed for each user based on the actual purchase information received from the register 14.

When the user leaves the store 200, the user approaches the gate device 13 for leaving the store. When the user approaches the gate device 13, the user terminal 15 communicates with the gate device 13 by short-range wireless communication. At this time, the flag information indicating that the shopping is completed is transmitted to the gate device 13 together with the user identification information of the user, and the identification information and the flag information are transmitted from the gate device 13 to the server via the communication network N1. Transferred to device 11. As a result, the server device 11 recognizes that the shopping has been completed without fraud and that the user has left the store.

As described above, the user can perform shopping using the shopping application at the store 200.

As described above, in the information processing system 100, the recommendation process for specifying the recommendation information according to the user is executed, and the specified recommendation information is displayed on the user terminal 15.

Hereinafter, a specific configuration of the information processing system 100 for realizing the recommendation processing will be described with reference to FIG.

[User terminal 15]
As shown in FIG. 3, the user terminal 15 includes a control unit 21, an operation display unit 22, a storage unit 23, an imaging unit 24, a communication I / F 25, and the like. The user terminal 15 is, for example, a mobile terminal owned by a user of the store 200, for example, a smartphone, a mobile phone, or a tablet terminal. The user terminal 15 may be a mobile terminal lent from the store 200, or may be a cart terminal installed in a shopping cart.

The imaging unit 24 is a digital camera that captures an image of a subject and outputs it as digital image data. A user who makes a purchase in the store 200 takes an image of the information code attached to the product to be purchased by the image pickup unit 24. By reading the captured image of the information code by the reading processing unit 211 described later, price information (product name, amount of money, product ID, etc.) of the product to be purchased can be obtained.

The communication I / F 25 connects the user terminal 15 to the communication network N1 by wire or wirelessly, and executes data communication according to a predetermined communication protocol with an external device such as a server device 11 via the communication network N1. It is a communication interface for In addition, the communication I / F 25 enables the user terminal 15 to perform data communication with devices such as gate devices 12 and 13 and registers 14 via radio (for example, short-range radio such as Bluetooth).

The operation display unit 22 is a user interface including a display unit such as a liquid crystal display or an organic EL display that displays various information, and an operation unit such as a mouse, keyboard, or touch panel that accepts user operations. The recommendation information according to the user is displayed on the display unit of the operation display unit 22.

The storage unit 23 is a non-volatile storage medium such as a flash memory that stores various types of information. The storage unit 23 stores a control program for causing the control unit 21 to execute various processes.

In addition, the storage unit 23 stores user identification information for identifying the user. The user identification information is information for identifying a user, such as an ID number, a name, a gender, and an age. The user identification information is registered in advance in the server device 11 provided in the store 200, and is stored and managed in the storage unit 32 (customer information storage unit 321) in the server device 11 together with the purchase history information.

Further, the storage unit 23 stores the price information of the product to be purchased, which is read by the reading processing unit 211 described later.

The control unit 21 has control devices such as a CPU, a ROM, and a RAM. The CPU is a processor that executes various arithmetic processes. The ROM is a non-volatile storage unit in which control programs such as a BIOS and an OS for causing the CPU to execute various processes are stored in advance. The RAM is a volatile or non-volatile storage unit that stores various types of information, and is used as a temporary storage memory (work area) for various processes executed by the CPU. Then, the control unit 21 controls the user terminal 15 by executing various control programs stored in advance in the ROM or the storage unit 23 on the CPU.

Specifically, as shown in FIG. 3, the control unit 21 includes various types such as a reading processing unit 211, a display processing unit 212, a notification processing unit 213 (an example of a transmission processing unit of the present invention), and an action result transmission unit 214. Includes processing unit. The control unit 21 functions as the various processing units by executing various processes according to the control program on the CPU. Further, a part or all of the processing units included in the control unit 21 may be composed of an electronic circuit. The control program may be a program for causing a plurality of processors to function as the various processing units.

The reading processing unit 211 reads the price information (product name, amount of money, product ID, etc.) of the product included in the information code based on the image data of the information code captured by the imaging unit 24. Hereinafter, for convenience of explanation, the price information read as a purchase target is referred to as purchase target information. This purchase target information is information about a product selected from a plurality of products in the store 200 as a purchase target by the user of the store 200. The read purchase target information is stored in the storage unit 23 until it is canceled or the settlement of the purchase target product is completed.

The display processing unit 212 causes the display unit of the operation display unit 22 to display the recommendation information transmitted from the server device 11. For example, the display processing unit 212 displays the recommendation information on the display unit of the operation display unit 22 in a pop-up format. When the recommendation information includes a product image, a product name, or the like, the display processing unit 212 displays such information on the display unit of the operation display unit 22 in a pop-up format. The product image or product name is linked to, for example, an address in which more detailed information on the recommended product (for example, product description, product price, product display location in the store 200) is stored, and is used. When a person touches the product image or product name on the display screen, the display processing unit 212 reads out the detailed information stored in the address and displays it on the display unit. Further, when the recommendation information includes the URL of the WEB site including the photographic image and the description of the product, the display processing unit 212 displays the URL on the display unit of the operation display unit 22. In this case, when the user touches the URL, the display processing unit 212 accesses the URL and displays the WEB site on the display unit.

The notification processing unit 213 transmits various information to the server device 11, the gate devices 12, 13 and the register 14. For example, the notification processing unit 213 transmits the user identification information or the like to the gate device 12 when the user enters the store 200, and uses the gate device 13 when the user leaves the store 200. Send person identification information, etc.

In addition, the notification processing unit 213 transmits the purchase target information read during the purchase to the server device 11. This transmission process is performed each time the purchase target information is read. That is, when the user uses the imaging unit 24 to image the information code of the product to be purchased and the reading processing unit 211 performs the reading process of reading the purchase target information, the purchase target information is immediately notified. It is transmitted to the server device 11 by the unit 213. Further, the notification processing unit 213 transmits the order information indicating the scan order (selection order) in which the purchase target information is read to the server device 11 together with the purchase target information in association with the purchase target information. The scanning order is the order in which the user scans the products in the store 200, and is the order in which the user selects the products as the purchase target (selection order). The scan order is counted by the control unit 21 each time the reading process is performed, and the order information indicating the counted order is added to the header unit or the like of the purchase target information. The server device 11 that has received the purchase target information stores the purchase target information in the purchase target product storage unit 323.

Further, when the purchase target information is canceled during the purchase, the notification processing unit 213 transmits the cancellation information (cancellation information) indicating that the purchase target information has been canceled to the server device 11. The server device 11 that has received the cancellation information deletes the purchase target information corresponding to the cancellation information from the planned purchase product storage unit 323.

The action result transmission unit 214 sets the action result indicating whether or not the user has acted on the recommendation information displayed on the display unit of the operation display unit 22 as the ranking determination unit 33 of the server device 11 (see FIG. 3). ). The actions include, for example, an action of browsing the recommendation information displayed on the display unit of the operation display unit 22 (browsing action), and an action of reading the product information of the product information code indicated by the recommendation information by the reading processing unit 211. (Reading behavior), or the behavior of purchasing the product indicated by the recommendation information displayed on the display unit (purchasing behavior), and the like can be mentioned. The action result includes a positive result indicating that each of the actions has occurred, or a negative result indicating that each of the actions has not occurred.

The control unit 21 performs a process of determining whether or not the user has taken an action with respect to the recommendation information displayed on the display unit of the operation display unit 22. The control unit 21 that performs such a determination process can be regarded as an action determination unit that determines whether or not the user has acted on the recommendation information.

For example, in the control unit 21, whether or not the product image or the product name is touch-operated between the time when the recommendation information is displayed on the display unit of the operation display unit 22 and the time when a certain time (time-up time) elapses. Or, a process of determining whether or not the URL has been touch-operated is performed. In this case, if it is determined that the touch operation is performed within the fixed time, the action result transmission unit 214 is the information of the affirmative result (action result) indicating that the user has browsed the recommendation information on the user terminal 15. Is transmitted to the ranking determination unit 33 of the server device 11.

In addition, whether or not the product information of the product information code indicated by the recommendation information has been read by the reading processing unit 211 until the fixed time elapses or the settlement processing is performed. Performs the process of determining whether or not. In this case, when it is determined that the product information of the product information code indicated by the recommendation information has been read, the action result transmission unit 214 is scheduled to purchase the product indicated by the recommendation information by the user of the user terminal 15. Information on the affirmative result (action result) indicating that there is is transmitted to the ranking determination unit 33 of the server device 11.

In addition, the control unit 21 performs a process of determining whether or not the product indicated by the recommendation information has been purchased. In this case, when the post-purchase product that has been settled includes the product indicated by the recommendation information, the action result transmission unit 214 shows an affirmative result indicating that the product indicated by the recommendation information has been purchased. The information (action result) is transmitted to the ranking determination unit 33 of the server device 11.

In addition, when the browsing action or the reading action is not performed in the fixed time, the action result transmitting unit 214 does not perform the reading action until the user performs the settlement process in the register 14. When the purchase action is not performed in the settlement process, information on a negative result (action result) indicating that each action has not occurred is transmitted to the ranking determination unit 33 of the server device 11.

[Cooking recipe database 17]
The cooking recipe database 17 is a storage unit that stores product information used for cooking and cooking recipes in association with each other. The cooking recipe database 17 stores a large amount of cooking recipe data using products such as various ingredients and seasonings. The cooking recipe database 17 is configured as an external device such as another server device or storage device capable of data communication with the server device 11 via the communication network N1 or the Internet. The server device 11 reads a cooking recipe from the cooking recipe database 17 as needed. The cooking recipe database 17 may be a storage unit such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive) provided in the server device 11.

[Server device 11]
The server device 11 is a server computer including a control unit 31, a storage unit 32, a ranking determination unit 33, a recipe selection unit 36 (an example of the cooking recipe selection unit of the present invention), a communication I / F35, and the like. The server device 11 is not limited to one computer, and may be a computer system in which a plurality of computers operate in cooperation with each other. Further, various processes executed by the server device 11 may be distributed and executed by one or a plurality of processors.

The communication I / F 35 connects the server device 11 to the communication network N1 by wire or wirelessly, and is predetermined between the user terminal 15, the gate devices 12, 13 and the register 14 via the communication network N1. It is a communication interface for executing data communication according to a communication protocol.

The storage unit 32 is a non-volatile storage unit including a semiconductor memory, an HDD (Hard Disk Drive), an SSD (Solid State Drive), or the like that stores various types of information. In the present embodiment, the configuration in which the storage unit 32 is provided in the server device 11 is illustrated. For example, a part or all of various information in the storage unit 32 is transmitted to the server device 11 through the communication network N1 or the Internet. It may be stored in an external device such as another server device or storage device capable of data communication with. In this case, the server device 11 reads necessary information from the external device or stores the information in the external device, if necessary.

The storage unit 32 stores a control program for causing the control unit 31 to execute various control processes and the recommendation process (recommendation extraction process, recommendation selection process) described later shown in FIG. 7. For example, the control program is non-temporarily recorded on a computer-readable recording medium such as a CD or DVD, and is read by a reading device (not shown) such as a CD drive or a DVD drive included in the server device 11. It is stored in the storage unit 32.

Further, the storage unit 32 stores information such as the set number and the set time used for the determination process in the recommendation process described later.

The storage unit 32 is divided into a plurality of storage areas. Specifically, the storage unit 32 is provided with a customer information storage unit 321 as an action history storage unit, a product information storage unit 322, a product storage unit 323 to be purchased, and a priority storage unit 324 as a priority storage unit. Has been done.

The customer information storage unit 321 stores information registered in advance for each user (hereinafter, referred to as customer information). The customer information includes purchase history information regarding products that the user has purchased at the store 200 in the past, in addition to the user identification information including the user's ID number, name, gender, age, and the like. That is, the purchase history information is information indicating the user's behavior history with respect to the product sold at the store 200.

The customer information is stored (registered) as the user identification information in the customer information storage unit 321 of the storage unit 32 when the user registers as a member of the store 200, for example. After that, when the user purchases a product in the store 200, the customer is in a state where the purchase history information including the product information and the purchase date related to the purchased product is linked to the user identification information of the purchased user. It is overwritten and stored in the information storage unit 321. That is, the customer information is updated. The purchase history information is used for the recommendation extraction process by the recommendation extraction process unit 311 described later.

The product information storage unit 322 stores product information related to all products that can be sold at the store 200. The product information is information that can identify the product, and includes, for example, price information including a product name, a price of the product, and a product ID (JAN code, etc.). In addition, the product information includes the type of product, the life of the product (expiration date, expiration date, expiration date, etc.), the presence or absence of a discount, the discount rate, the display location of the product, the photograph and description of the product, and the like. Information such as a URL includes information that is convenient for the user when shopping at the store 200. If the product is a cooked food (processed food) such as prepared foods, the cooking time (including the cooking date and scheduled cooking time), which is the processing date and time of the cooked food, and the state after cooking (processed state). Information indicating the above may be included in the product information. Further, when the product is, for example, the target of the sales promotion campaign, the product information may include information for determining whether or not the product is the target of the sales promotion campaign. Furthermore, the product information may include information that should be grasped only by the seller of the store 200, for example, the profit margin of the product, the degree of disposal risk, the number of stocks, and the like.

In addition, the product information storage unit 322 stores the past sales record and the past disposal history for each product. The past sales record includes the date and time when the product was sold in the past, the price, the number of sales, the presence or absence of a discount, the discount rate, and the like. In addition, the past disposal history includes the presence or absence of disposal of the unsold product, the date and time of disposal performed in the past, the amount of disposal, and the like.

The product information stored in the product information storage unit 322 is updated every time a change occurs. For example, when the user pays for the product (settlement), the inventory quantity of the product is immediately updated by the control unit 31 of the server device 11. In addition, the price of the product, the number of stocks, the presence or absence of a discount, the discount rate, the cooking time, the presence or absence of a sales promotion campaign, the exhaust risk, the increase in the number of stocks due to arrival, etc. are based on the information input by the employee from the employee terminal 16. Is updated by the control unit 31.

The purchase target information sequentially transmitted from the user terminal 15 is temporarily stored in the product storage unit 323 to be purchased each time the reading process is performed by the reading processing unit 211. The planned purchase product storage unit 323 functions as a virtual shopping cart. The purchase target information is stored in the planned purchase product storage unit 323 until the purchase of the product is canceled or the settlement of the purchase target product is completed. Further, in the purchase target product storage unit 323, the scan order (selection order) transmitted along with the purchase target information is stored in a state associated with the purchase target information.

The priority storage unit 324 stores a plurality of product information as well as priorities relating to the sale of the plurality of products. FIG. 5 is a ranking list TB1 showing the priority of each of the plurality of products. In the ranking list TB1, among all the products stored in the product information storage unit 322, a plurality of products (hereinafter referred to as priority products) that the store 200 side (seller) desires to sell with priority are included. It is included and prioritizes sales for each priority product. The priority order indicates the order of the products for which sales are desired to be promoted, and the product having the highest order is the product for which sales are most desired to be promoted in the store 200. The priority may be set for each of the products stored in the product information storage unit 322.

The priority of each of the priority products in the ranking list TB1 is determined based on the fluctuation information regarding the fluctuation factors that cause fluctuations in the priority. The fluctuation information includes, for example, the price, type, life span, presence / absence of discount, discount rate of the priority product, cooking time of the cooked food such as prepared food, and whether or not the product is subject to the sales promotion campaign. Information such as profit margin, degree of disposal risk, inventory quantity, past sales performance, and past disposal history. Further, the fluctuation information includes the cooking date, the cooking time, and the state after cooking when the priority product is a cooked food typified by prepared foods. In addition, the fluctuation information includes temperature, humidity, atmospheric pressure, and weather at the location of the store 200. In addition, the fluctuation information includes the current time, the number of visitors to the store 200 on the day, and the visitor history. The store visitor history is statistical information indicating the number of visitors by month or day of the week in the past. In addition, the number of visitors includes the expected number of visitors predicted from the visitor history. It can be said that such fluctuation information is information that causes fluctuations in the situation (product status) surrounding the product, including the state of the product and the purchase motivation of the user. In determining the priority order of the priority product, the variation information used in the determination process may include any one or more of the above-mentioned specific plurality of variation elements.

The priority order varies depending on the product status and various factors on the store 200 side (seller). For example, a product with a large inventory is given a higher priority, and a product with a small inventory is given a lower priority. This is because the larger the number of stocks, the more likely it is that unsold products will occur. In addition, products with a short product life are set at the top, and products with a long product life are set at the bottom. Products with a high rate of return are ranked high, and products with a low profit margin are ranked low. Products with a high disposal risk are ranked high, and products with a low risk of disposal are ranked low. In addition, the priority order varies depending on the type of product. For example, ingredients / foodstuffs (including seasonings), foods (including cooked foods), and beverages that are ingredients for cooking are set at the top. Detergents, stationery, kitchen utensils, etc. are set at the bottom. In addition, even for cooked foods such as prepared foods, the priority order varies depending on what time the cooking time is or the state after cooking, and the elapsed time after cooking is long or until the cooking time. If the waiting time is long, if the state after cooking is bad, it is ranked high, and if the elapsed time is short, the waiting time is short, or the state after cooking is good, it is ranked low.

In addition, the price of the product, the presence or absence of a discount, the discount rate, the past sales record, the past disposal history, the temperature, humidity, atmospheric pressure, and weather at the location of the store 200, the number of visitors, the visitor history, etc. are also priorities. Is a factor that fluctuates. Further, when a plurality of fluctuation information exists, the plurality of fluctuation information described above may affect each other and the priority may change. For example, a large number of visitors are expected on a sunny day, so in this case, the ranking of each priority product is determined by focusing on the effect of the profit margin rather than the effect of the number of inventories. In addition, when the weather is good but the temperature is high, the ranking is determined by emphasizing the type of product. For example, if it is a cooked food, it is presumed that it is difficult to sell from the past sales results. Cooked foods that are kept warm are ranked high, and cold dishes that are presumed to sell well are ranked low.

In the present embodiment, the priority order is determined or updated by the order determination unit 33, which will be described later, based on the plurality of fluctuation information described above. The ranking determination unit 33 will be described later.

[Control unit 31]
The control unit 31 has control devices such as a CPU, a ROM, and a RAM. The CPU is a processor that executes various arithmetic processes. The ROM is a non-volatile storage unit in which control programs such as a BIOS and an OS for causing the CPU to execute various arithmetic processes are stored in advance. The RAM is a volatile or non-volatile storage unit that stores various types of information, and is used as a temporary storage memory (work area) for various processes executed by the CPU. Then, the control unit 31 controls the server device 11 by executing various control programs stored in advance in the ROM or the storage unit 32 on the CPU.

Specifically, as shown in FIG. 3, the control unit 31 includes a recommendation extraction processing unit 311, a recommendation selection processing unit 312 (an example of a recommended information specifying unit of the present invention), and a recommendation information transmitting unit 313 (recommended information of the present invention). Output unit), Information acquisition unit 314 (Purchase target information acquisition unit of the present invention, Cancellation information acquisition unit), Recipe selection processing unit 315 (Cooking recipe acquisition unit of the present invention), Missing product determination unit 316 (An example of a lacking product determination unit of the present invention), and various processing units are included. The control unit 31 functions as the various processing units by executing various processes according to the control program on the CPU. Further, a part or all of the processing units included in the control unit 31 may be composed of an electronic circuit. The control program may be a program for causing a plurality of processors to function as the various processing units.

The information acquisition unit 314 acquires the purchase target information transmitted from the user terminal 15. The notification processing unit 213 of the user terminal 15 transmits the purchase target information read during the purchase to the server device 11 each time the purchase target information is read. At this time, the order information indicating the scan order (selection order) in which the purchase target information is read is also added to the purchase target information and transmitted. In the server device 11, the purchase target information is acquired by the information acquisition unit 314.

In addition, the information acquisition unit 314 acquires the cancellation information transmitted from the user terminal 15. When the purchase target information is canceled during the purchase, the notification processing unit 213 of the user terminal 15 transmits the cancellation information to the server device 11. In the server device 11, the cancellation information is acquired by the information acquisition unit 314. The server device 11 that has acquired the cancellation information deletes the purchase target information corresponding to the cancellation information from the planned purchase product storage unit 323.

In addition, the information acquisition unit 314 acquires the priority regarding the sale of a plurality of products provided at the store 200 from the priority storage unit 324. Specifically, the information acquisition unit 314 acquires the priority of the necessary products from the priority storage unit 324. More specifically, when the product information of a plurality of recommended product candidates (recommended product candidates) presumed to match the user's taste is selected by the recommendation extraction process by the recommendation extraction processing unit 311, the information acquisition unit 314 acquires the priority of the selected plurality of product information from the priority storage unit 324.

In addition, the information acquisition unit 314 acquires the user's purchase history information for the product provided in the store 200 from the customer information storage unit 321. Specifically, when the user identification information of the user is sent from the gate device 12 when the user visits the store, the information acquisition unit 314 transfers the customer information corresponding to the user identification information to the customer information. The purchase history information extracted from the storage unit 321 and included in the customer information is extracted.

The recommendation extraction processing unit 311 executes a recommendation extraction process for extracting recommendation information suitable for the user's taste from a plurality of product information based on the purchase history information of the user stored in the customer information storage unit 321. .. As a control program for executing the recommendation extraction process, the storage unit 32 stores a recommendation engine (recommendation program) that extracts the recommendation information by using a conventionally known predetermined recommendation algorithm that uses the purchase history information. ing. The recommendation extraction processing unit 311 uses the recommendation engine to extract a preset number of recommended product candidates of two or more from a plurality of product information. That is, the recommendation extraction processing unit 311 executes the recommendation extraction processing based on a predetermined algorithm by using the recommendation engine stored in the storage unit 32.

The recommendation selection processing unit 312 executes a recommendation selection process for selecting a specific recommended product candidate. A control program for executing the recommendation selection process is stored in the storage unit 32. The recommendation selection processing unit 312 transmits the purchase target information based on the purchase target information acquired by the information acquisition unit 314 and the ranking information indicating the scan order (selection order) in which the purchase target information is read. A process of selecting recommended product information according to the user who uses the user terminal 15 from a plurality of product information stored in the product information storage unit 322 is performed. In the present embodiment, the recommendation selection processing unit 312 selects the recommended product information from a plurality of product information in the product information storage unit 322 based on the purchase target information up to the preset setting order in which the scan order is predetermined. To do. Further, the recommendation selection processing unit 312 selects the recommended product information by using the priority of the priority product stored in the priority storage unit 324 in addition to the purchase target information and the ranking information. ..

When the information acquisition unit 314 acquires the cancellation information transmitted from the user terminal 15, the recommendation selection processing unit 312 excludes the canceled products indicated by the cancellation information. And the ranking information, the processing of selecting the recommended product information from the plurality of product information is performed.

The recommendation information transmission unit 313 outputs the recommendation information including the product information of the specific recommended product candidate selected by the recommendation selection processing unit 312 to the user terminal 15 through the communication network N1. When the user terminal 15 receives the transmitted recommendation information, the user terminal 15 displays the recommendation information on the operation display unit 22 of the user terminal 15. In addition, the recommendation information transmission unit 313 also transmits the recommendation information to the employee terminal 16.

The recipe selection processing unit 315 selects and acquires a cooking recipe that uses a high-ranking product corresponding to the high-ranking order up to the set ranking acquired by the information acquisition unit 314 from the cooking recipe database 17. The recipe selection processing unit 315 may select one or more cooking recipes. Since the cooking recipe selected by the recipe selection processing unit 315 uses the product selected by the user as the purchase target, it can be said that the cooking recipe matches the product selected by the user.

The deficient product determination unit 316 compares the product used in the cooking recipe selected by the recipe selection processing unit 315 with the high-ranking product, and determines the deficient product in the dish indicated by the selected cooking recipe. To do. In addition to the cooking recipe, the cooking recipe database 17 is associated with product information such as ingredients used in the cooking recipe. Therefore, the deficient product determination unit 316 reads the product information corresponding to the selected cooking recipe from the cooking recipe database 17, and determines the deficient product excluding the higher-ranking product from the read product information.

[Ranking unit 33]
Hereinafter, the ranking determination unit 33 will be described with reference to FIG. The ranking determination unit 33 is a learning device configured to determine the priority by machine learning, and has a learning model for determining the priority. Here, FIG. 4 is a block diagram showing the configuration of the ranking determination unit 33, and shows an example in which reinforcement learning is applied as a machine learning algorithm.

As shown in FIG. 4, the ranking determination unit 33 includes a fluctuation information observation unit 331 (variation information acquisition unit), an action result acquisition unit 332 (action result acquisition unit), a learning unit 40, and a data update processing unit 333. , Equipped with. The ranking determination unit 33 can use a general-purpose CPU, but uses, for example, GPGPU (General-Purpose computing on Graphics Processing Units), a large-scale PC cluster, or the like in order to enable higher-speed arithmetic processing. Is desirable.

The fluctuation information observation unit 331 acquires the fluctuation information used for determining the priority of each of the priority products shown in the ranking list TB1 of FIG. The fluctuation information is the price of the product, the type of the product, the life of the product (expiration date, expiration date, expiration date, etc.), whether or not there is a discount, the discount rate, the cooking time or scheduled cooking time of the cooked food, and the target of the sales promotion campaign. In the case of the determination information of whether or not the product, the profit margin of the product, the degree of disposal risk, the number of stocks, the past sales record, and the past disposal history, the fluctuation information observation unit 331 performs the product information in the product information storage unit 322. Is monitored, and real-time information is constantly acquired from the product information storage unit 322.

When the fluctuation information is the temperature, humidity, and atmospheric pressure at the location of the store 200, the fluctuation information observation unit 331 is output from the temperature sensor, humidity sensor, and atmospheric pressure sensor provided indoors or outdoors of the store 200. Receives the sensor output value and acquires the real-time temperature, humidity, and atmospheric pressure indicated by the sensor output value. When the fluctuation information is the weather around the store 200, the control unit 31 downloads the weather information from the weather information database when the server device 11 is connected to the Internet, and the fluctuation information observation unit 331 is connected to the control unit 31. Receive the weather information.

The acquired fluctuation information is information used for learning of the learning unit 40, and is stored in a storage unit (not shown) in the ranking determination unit 33. The fluctuation information is input from the storage unit to the learning unit 40.

The action result acquisition unit 332 acquires the action result information transmitted from the action result transmission unit 214 of the user terminal 15. That is, the action result acquisition unit 332 acquires the action result (affirmative result, negative result) indicating whether or not the user has browsed or purchased the recommended product indicated by the recommendation information. The acquired action result information is information used for learning of the learning unit 40, and is stored in a storage unit (not shown) in the ranking determination unit 33. The action result is input from the storage unit to the learning unit 40.

The learning unit 40 learns the priority order based on the fluctuation information acquired by the fluctuation information observation unit 331. In the present embodiment, the learning unit 40 uses not only the acquired fluctuation information but also the action result acquired by the action result acquisition unit 332, and the store 200 side preferentially sells the product in the priority order. Machine learning. The learning unit 40 will be described later.

The data update processing unit 333 refers to the priority order learned by the learning unit 40, and refers to the priority order stored in the priority order storage unit 324, and in detail, each of the priority products shown in the order list TB1 of FIG. Update the priority of to the order after learning.

The learning unit 40 extracts useful rules, rules, knowledge representations, judgment criteria, etc. in the set of the input fluctuation information by analysis, outputs the judgment result, and learns the knowledge. It has a function. Machine learning includes algorithms such as supervised learning, unsupervised learning, and reinforcement learning, and in order to realize these methods, the feature quantity itself is extracted. A technique called "deep learning" is used for learning.

Here, supervised learning is an algorithm that learns the "relationship between input and output" from data input in advance. The input data is given the correct answer of the data together with the input value, and by giving a large amount of such data to the learning unit 40, the learning unit 40 learns the features in those data. , Estimate the output (result) from the input. If the relationship between given input / output data can be learned, the output can be predicted by applying the relationship to unknown data.

Unsupervised learning is an algorithm that learns features such as the structure, characteristics, and new knowledge of data from a large amount of input data without being given output data that is the correct answer. It differs from supervised learning in that the correct answer is not given to the data that is the source of learning.

In addition, intensive learning is not learning based on fixed and clear data such as supervised learning and unsupervised learning, but the program itself observes a given environment (current state) and is a continuous series. It is an algorithm that evaluates the behavior of the above and learns the appropriate behavior based on the interaction that the behavior gives to the environment, that is, the behavior to maximize the reward obtained in the future. TD learning and Q-learning are known as typical methods.

In reinforcement learning, the consequences of behavior are unknown. Therefore, when reinforcement learning is adopted as machine learning of the learning unit 40, learning starts from a state in which the priority of each product to be learned is not known at all, and in the initial stage, the priority obtained by learning is obtained. The ranking may not be the ranking desired by the store 200. Therefore, it is desirable to perform pre-learning by supervised learning, set the pre-learned priority as the initial state, and then perform reinforcement learning.

For example, when the reinforcement learning in the learning unit 40 is Q-learning, the general update formula (behavior value table) of the action value function Q (s, a) is expressed by the following formula (1).

In the equation (1), s _t represents the environment at time t, a _t represents the action at time t. By the action a _t, the environment is changed to s _{t + 1.} rt _{+ 1} is a reward that can be obtained by changing the environment. The term with max is the Q value multiplied by γ when the action a with the highest Q value known at that time is selected under _{the environment st + 1.} Further, γ is called a discount rate, and is a parameter of 0 <γ ≦ 1. Further, α is a learning coefficient in the range of 0 <α ≦ 1. When Q-learning is applied, the behavior of browsing the recommendation information displayed on the user terminal 15, reading the product information code indicated by the recommendation information, or the user purchasing the product (browsing behavior, reading behavior, purchase behavior) becomes the action a _t.

As shown in FIG. 4, the learning unit 40 includes a reward calculation unit 401 (an example of a reward output unit of the present invention) and a value function update unit 402 (an example of a learning model update unit of the present invention). The reward calculation unit 401 calculates and outputs a reward based on the fluctuation information acquired by the fluctuation information observation unit 331. Further, the value function update unit 402 updates the value function related to the priority based on the fluctuation information and the reward calculated by the reward calculation unit 401. This value function corresponds to the learning model.

As described above, the fluctuation information changes in the priority order, but the fluctuation information itself changes from moment to moment. Therefore, when the fluctuation information changes, the priority order is also updated. Whether or not the priority after the change is appropriate can be evaluated by whether the action result of each action of browsing action, reading action, and purchasing action is a positive result or a negative result. Thus, for example, the case of applying the Q-learning, action result (positive result, a negative result) is action a _t in substantially formula (1), action value represented by the formula (1) function Q (s the a), is used as a value function for changing the action a _t.

In the present embodiment, the reward calculation unit 401 outputs a positive reward when the action result is a positive result indicating that the recommended product indicated by the recommendation information has been viewed or purchased, and the action result is the recommended product. Outputs a negative reward if the result is negative, indicating that the item was not viewed or purchased. The absolute value of the output reward may differ depending on the content of the action result. For example, the reward for the behavioral result of the browsing behavior may be set to the lowest, and the reward corresponding to the behavioral result of the purchasing behavior may be set to the highest. Further, a weighting coefficient for the reward may be set for each user. For example, when the reward based on the action result of the user who frequently uses the store 200 is emphasized, the weighting coefficient multiplied by the reward is used as the usage frequency. It may be set to a proportional value.

Hereinafter, using the flowchart of FIG. 6, the recommended information specifying method of the present invention will be described together with a first processing example of the recommendation processing executed by the control unit 31 of the server device 11. In the following description, it is assumed that the recommendation process is performed from the time when the user passes through the gate device 12 of the store 200 to the time when the user leaves the store after passing through the gate device 13 of the store 200. .. That is, the recommendation process is performed when the user is buying around in the store 200. In FIG. 6, S11, S12, ... Indicates a processing procedure number (step number).

First, when the user enters the store 200, the control unit 31 acquires the user identification information transmitted from the user terminal 15 of the user who entered the store. As a result, the control unit 31 can identify the user who has entered the store.

In step S11, the control unit 31 acquires the purchase target information transmitted from the user terminal 15. The purchase target information is transmitted and acquired each time the user reads the information code of the product picked up by the user terminal 15. Such processing is performed by the information acquisition unit 314 of the control unit 31. Step S11 corresponds to the purchase target information acquisition step of the present invention.

In the next step S12, the purchase target information acquired by the information acquisition unit 314 is stored in the purchase planned product storage unit 323 of the storage unit 32. As described above, the purchase target information is associated with rank information indicating the scan order (selection order) in which the purchase target information is read. Therefore, the control unit 31 can obtain the ranking information by checking the header unit of the purchase target information. If the order information is not associated with the purchase target information, the control unit 31 may count the number of times the purchase target information is received each time. The counted number of receptions is the number of times the user has read the information code, and indicates the order in which the purchase target information has been sent, that is, the scanning order in which the information code has been read.

Next, in step S13, the control unit 31 determines whether or not the number of products of the product that the user plans to purchase has reached the set number. The set number is an arbitrary threshold value used for the determination in step S13. This number of settings corresponds to the setting order. The control unit 31 determines the current number of products based on the ranking information of the purchase target information finally stored in the product storage unit 323 to be purchased, and compares the number of products with the set number. In step S13, when it is determined that the number of products has reached the set number (Yes side of S13), the process proceeds to step S14. On the other hand, in step S13, when it is determined that the number of products is less than the set number (No side of S13), the process proceeds to step S15.

In step S14, the control unit 31 selects a cooking recipe using the product (hereinafter, referred to as a higher-ranking product) indicated by the purchase target information from the cooking recipe database 17 based on the set number of purchase target information. The recipe selection process to be acquired is performed. Such processing is performed by the recipe selection processing unit 315 of the control unit 31. In the present embodiment, the control unit 31 selects a cooking recipe containing the higher-level product as a main ingredient from the cooking recipe database 17.

The high-ranking product is a product selected as a purchase target shortly after the user enters the store. Therefore, it can be said that these high-ranking products are products that the user has decided to purchase from the beginning of entering the store, and are products that the user has decided to purchase without worrying about purchasing the product. On the other hand, products that exceed the set number are products that the user decides to purchase after a considerable amount of time has passed since the user entered the store, and they are not planning to purchase from the beginning of the store and decide while buying around. It can be estimated that it was done. Therefore, it can be said that the cooking recipe using the higher-ranking product selected in step S14 is a cooking recipe that matches the product selected by the user and the taste of the user.

In step S15, the control unit 31 determines whether or not the time interval (corresponding to the selection time of the present invention) when the user sequentially reads the information codes of a plurality of products is equal to or longer than the preset set time. .. The time interval is the time spent from the selection of the previous product to the selection of the next product. Further, the set time is an arbitrary threshold value used for the determination in step S15. The time interval indicates the time from reading the information code of the previous product to the decision to purchase the next product, and the time spent until the user selects the product to be purchased next. Corresponds to. If the time interval is less than the set time, it means that the user has decided the next product without much trouble, which means that, for example, the user is not troubled with the meal menu. Can be estimated. In this way, when the time interval is less than the set time, there is a possibility that the next product to be purchased may be selected without worrying, so that the processes after step S11 are performed until the number of products reaches the set number. Repeated.

On the other hand, if the time interval is equal to or longer than the set time, it means that the user has trouble before deciding the next product, for example, in a situation where the user is troubled with the menu of meals. It can be estimated that there is. As described above, when the time interval is equal to or longer than the set time, it can be presumed that the products purchased after that are likely to be products not related to the menu. In this case, without waiting for the number of products to reach the set number, based on the information obtained at the present time, which is less than the set number, excluding the last acquired purchase target information. The recipe selection process in step S14 is performed. That is, a process of selecting a cooking recipe that uses a product higher than the ranking indicated by the ranking information of the purchase target information acquired last is performed.

In the next step S16, the control unit 31 compares the product used in the cooking recipe selected in step S14 with the higher-ranking product, and determines the insufficient product in the cooking indicated by the cooking recipe. Here, if it is determined that there is no missing product, the process proceeds to step S17, the control unit 31 performs the same recipe selection process (recipe reselection process) as in step S14, and prepares another cooking recipe in the cooking recipe database 17. Select from and obtain.

When it is determined in step S16 that there is a shortage product, the control unit 31 identifies the shortage product as a recommended product that matches the taste of the user, and product information related to the shortage product (hereinafter, shortage product). Information) is extracted from the product information storage unit 322 (S18). The deficient product information is product information including price information of the deficient product and the like. The processing of step S16 is performed by the recommendation selection processing unit 312 of the control unit 31. Step S16 corresponds to the recommended information specifying step of the present invention.

After that, the recommendation information including the cooking recipe selected in step S14 and the insufficient product information is transmitted to the user terminal 15 of the user by the recommendation information transmission unit 313. On the user terminal 15, the received recommendation information is displayed on the display unit of the operation display unit 22. The recommendation information is also transmitted to the employee terminal 16.

As described above, in the present embodiment, as the recommendation information, the cooking recipe matching the user's taste and the missing product information are displayed on the user terminal 15. Therefore, the user can obtain a cooking recipe that matches his / her taste at the present time, and can easily decide the menu that could not be decided. In addition, it is possible to obtain product information that is lacking in the cooking recipe, and it is possible to prevent forgetting to buy products such as ingredients, seasonings, and kitchen items necessary for the decided menu. In addition, the store 200 side (seller) can promote sales of the shortage product, and thus can increase the purchase rate of the product.

Further, since the recommendation information is also transmitted to the employee terminal 16, the employee can confirm the received recommendation information of each user.

For example, when the scanned product to be purchased is canceled and the information acquisition unit 314 acquires the cancellation information transmitted from the user terminal 15, the cancellation information indicates in step S14. Based on the purchase target information excluding the canceled products, a process of selecting and acquiring cooking recipes using the products indicated by the purchase target information from the cooking recipe database 17 is performed.

Hereinafter, the recommended information specifying method of the present invention will be described with reference to a second processing example of the recommendation processing executed by the control unit 31 of the server device 11 using the flowchart of FIG. 7. The second processing example differs from the first processing example described above in that step S161 is added and the processing of step S181 is performed instead of step S18. Therefore, only the differences will be described below.

If it is determined in step S16 that there is a shortage product, the control unit 31 performs the process of step S161. In step S161, the control unit 31 determines whether or not the shortage product includes a product having a higher priority belonging to the order list TB1 of FIG. For example, the control unit 31 determines whether or not the shortage product is a product whose priority is within a predetermined reference order (10th in the present embodiment). The reference order is a threshold value for determining whether or not the priority order is higher, and can be arbitrarily determined.

In step S161, when it is determined that the shortage product is a product having the priority within the 10th place (Yes side of S161), the control unit 31 has the priority within the 10th place among the shortage products. A product is specified as a recommended product that matches the taste of the user, and product information related to the product is extracted from the product information storage unit 322 (S181).

On the other hand, in step S161, if it is determined that the shortage product is not a product whose priority is within the 10th place (No side of S161), the recipe reselection process of step S17 is performed, and steps S16 and subsequent steps are performed. The process is repeated.

Hereinafter, using the flowchart of FIG. 8, a method for specifying recommended information of the present invention will be described together with a third processing example of the recommendation processing executed by the control unit 31 of the server device 11. The difference between the third processing example and the first processing example described above is that steps S131 to S133 have been added. Therefore, only the differences will be described below.

When the process proceeds from step S13 or S15 to the next step S131, the control unit 31 acquires the purchase history information of the user who entered the store from the customer information storage unit 321. Such processing is performed by the information acquisition unit 314 of the control unit 31. Further, in the next step S132, the control unit 31 extracts the action content of the user from the purchase target information acquired in step S11 and the purchase history information acquired in step S131.

Next, in step S133, the control unit 31 uses the recommendation engine to generate a plurality of recommended recommended product candidates (recommended product candidates) that will match the user's taste based on the action content. Perform the extraction process. Such processing is performed by the recommendation extraction processing unit 311 of the control unit 31. In the present embodiment, the recommendation extraction processing unit 311 determines, for example, five candidates.

Subsequently, in step S14, the control unit 31 selects and acquires cooking recipes using the products indicated by these recommended product candidates from the cooking recipe database 17 based on the plurality of recommended product candidates extracted in step S133. Recipe selection process is performed.

Hereinafter, using the flowchart of FIG. 9, the recommended information specifying method of the present invention will be described together with a fourth processing example of the recommendation processing executed by the control unit 31 of the server device 11. The fourth processing example differs from the first processing example described above in that the processing in steps S14 to S18 is replaced by steps S131 to S191. Therefore, only the differences will be described below.

When the process proceeds from step S13 or S15 to the next step S131, the control unit 31 performs the processes of steps S131 to S133 of the third processing example described above.

After that, in the next step S162, the control unit 31 determines whether or not the plurality of recommended product candidates extracted in step S133 include products having a higher priority belonging to the ranking list TB1 of FIG. For example, the control unit 31 determines whether or not the plurality of recommended product candidates are products whose priority is within the 10th place.

In step S162, when it is determined that a product having a higher priority is included in the plurality of recommended product candidates (Yes side of S162), in the next step S182, among the plurality of recommended product candidates. Select the products with the highest priority from the above, and specify the selected products as recommended products. Such processing is performed by the recommendation selection processing unit 312 of the control unit 31. Step S182 corresponds to the recommended information specifying step of the present invention. After that, the recommendation information including the recommended product is transmitted to the user terminal 15 of the user by the recommendation information transmission unit 313 (S191). Then, on the user terminal 15, the received recommendation information is displayed on the display unit of the operation display unit 22. The recommendation information is also transmitted to the employee terminal 16.

On the other hand, in step S162, when it is determined that the product having a higher priority is not included in the plurality of recommended product candidates (No side of S162), the control unit 31 uses the recommendation engine again. , A candidate re-extraction process for extracting a plurality of recommended product candidates different from the candidates extracted in step S134 is performed based on the action content (step S163). After that, the process of step S162 is executed, and the processes of steps S162 and S163 are repeated until it is determined that the product having a higher priority is included in the plurality of recommended product candidates.

Hereinafter, an example of the learning operation flow of the learning unit 40 of the ranking determination unit 33 using reinforcement learning will be described with reference to the flowchart of FIG. In FIG. 10, S21, S22, ... Indicates a processing procedure number (step number).

First, in step S21, the action result acquisition unit 332 of the ranking determination unit 33 acquires the action result (action result of browsing action, reading action, purchasing action) transmitted from the user terminal 15. In this step S21, the action results of all the users who use the store 200 are transmitted from each of the user terminals 15.

In step S22, the reward calculation unit 401 of the learning unit 40 calculates a determination evaluation value for determining whether or not the current priority is appropriate based on the action result acquired in step S21. The judgment evaluation value is calculated by adding evaluation points determined for each content of the action result. For example, positive evaluation points are set for positive results of browsing behavior, reading behavior, and purchasing behavior, and negative evaluation points are set for negative results. The judgment evaluation value is calculated by adding the evaluation points for all the action results. When a weighting coefficient is set for the evaluation point for each user, for example, a weighting coefficient of a numerical value proportional to the usage frequency is set for the evaluation point for the action result of the user who frequently uses the store 200. If so, the determination evaluation value may be calculated in consideration of the weighting coefficient.

In the next step S23, it is determined whether or not the determination evaluation value is within a predetermined allowable range. If it is determined that the determination evaluation value is within the permissible range, the process proceeds to step S24, assuming that the current priority is appropriate, and a positive reward is set. On the other hand, if it is determined that the determination evaluation value exceeds the permissible range, the process proceeds to step S25 and a negative reward is set, assuming that the current priority is inappropriate.

After that, in step S26, the value function update unit 402 of the learning unit 40 updates the value function related to the priority, that is, the action value function Q (s, a), returns to step S21 again, and repeats the same process. Will be executed.

In the above-described embodiment, the information processing system 100 applied to the actual store 200 is illustrated, but the present invention is for a virtual store existing on the Internet where the user makes a purchase via the user terminal 15. Is also applicable.

The embodiments described above include the features described below.
(1) A purchase target information acquisition unit that acquires purchase target information for each product selected as a purchase target of the user at the store from a terminal device used by the user at the store.
Based on the ranking information regarding the selection order of the selected products and the purchase target information, the recommended information including the recommended products according to the user is specified from the plurality of product information regarding the plurality of products provided at the store. Recommended information identification unit, and a recommended information identification device.
(2) The recommendation according to (1), wherein the recommended information specifying unit specifies the recommended information from the plurality of product information based on the purchase target information regarding the higher-ranked products up to a predetermined setting order. Information identification device.
(3) A dish that selects and acquires a cooking recipe that uses the higher-ranked product corresponding to the higher-ranked order from the cooking recipe storage unit that stores the product information used for cooking and the cooking recipe in association with each other. Recipe selection department and
It is further provided with a shortage product determination unit that compares the products used in the cooking recipe acquired by the cooking recipe selection unit with the high-ranking products and determines the shortage products that are not used in cooking.
The recommended information specifying unit extracts the deficient product information related to the deficient product from the plurality of product information, and specifies the cooking recipe acquired by the cooking recipe selection unit and the deficient product information as the recommended information. The recommended information identification device according to (2) above.
(4) When the selection time from the selection of the previous product to the selection of the next product is longer than the predetermined set time, the cooking recipe selection unit determines the selection order of the next product. The recommended information identification device according to (3) above, which selects and acquires a cooking recipe that uses a higher-ranking product.
(5) The recommended information identification device according to (3) or (4) above, wherein the cooking recipe selection unit selects a cooking recipe whose main ingredient is the high-ranking product.
(6) Further provided with a cancellation information acquisition unit for acquiring cancellation information for canceling the selection of the product selected as the purchase target of the user from the terminal device.
From the above (1), the recommended information specifying unit specifies the recommended information from the plurality of product information based on the purchase target information and the ranking information from which the canceled products indicated by the cancellation information are excluded. The recommended information identification device according to any one of (5).
(7) In addition to the purchase target information and the ranking information, the recommended information identification unit also uses predetermined priorities for the sale of the plurality of products provided at the store, and the plurality of product information. The recommended information specifying device according to any one of (1) to (6) above, which specifies the recommended information from the above.
(8) The recommended information identification unit is related to the deficient products having a higher predetermined priority for the sale of a plurality of products provided at the store among the deficient products determined by the deficient product determination unit. The recommended information specifying device according to (3), wherein the missing product information is extracted and the cooking recipe acquired by the cooking recipe selection unit and the missing product information are specified as the recommended information.
(9) The recommended information specifying device according to any one of (1) to (8), further comprising a recommended information output unit that outputs the recommended information specified by the recommended information specifying unit to the terminal device.
(10) A purchase target information acquisition unit that acquires purchase target information for each product selected as a purchase target of the user at the store from a terminal device used by the user at the store.
Identification of recommended information that identifies recommended information according to the user from a plurality of product information related to a plurality of products provided at the store based on the ranking information regarding the selection order of the selected products and the purchase target information. Department and
A recommended information specifying system including a recommended information output unit that outputs the recommended information specified by the recommended information specifying unit to the terminal device.
(11) A purchase target information acquisition step of acquiring purchase target information for each product selected as a purchase target of the user in the store from a terminal device used by the user in the store.
Identification of recommended information that identifies recommended information according to the user from a plurality of product information related to a plurality of products provided at the store based on the purchase target information and ranking information regarding the selection order of the selected products. Steps and recommended information identification methods.
(12) A purchase target information acquisition step of acquiring purchase target information for each product selected as a purchase target of the user at the store from a terminal device used by the user at the store.
Identification of recommended information that identifies recommended information according to the user from a plurality of product information related to a plurality of products provided at the store based on the purchase target information and ranking information regarding the selection order of the selected products. A program that lets your computer perform steps and.

11: Server device 12: Gate device 13: Gate device 14: Register 15: User terminal 16: Employee terminal 17: Cooking recipe database 21: Control unit 22: Operation display unit 23: Storage unit 24: Imaging unit 25: Communication I / F
31: Control unit 32: Storage unit 33: Ranking determination unit 35: Communication I / F
36: Recipe selection unit 40: Learning unit 100: Information processing system 200: Store 211: Reading processing unit 212: Display processing unit 213: Notification processing unit 214: Action result transmission unit 311: Recommendation extraction processing unit 312: Recommendation selection processing unit 313: Recommendation information transmission unit 314: Information acquisition unit 315: Recipe selection processing unit 316: Insufficient product determination unit 321: Customer information storage unit 322: Product information storage unit 323: Purchased product storage unit 324: Priority storage unit 331: Fluctuation information observation unit 332: Action result acquisition unit 333: Data update processing unit 401: Reward calculation unit 402: Value function update unit

Claims (12)

A purchase target information acquisition unit that acquires purchase target information for each product selected as a purchase target of the user in the store from a terminal device used by the user in the store.
When a predetermined condition is satisfied for the selection of the product, the user is stored in the product information storage unit in which a plurality of product information related to the plurality of products provided at the store is stored based on the purchase target information. A recommended information identification device including a recommended information identification unit for specifying recommended information including recommended products according to the above. A cooking recipe acquisition unit that acquires a cooking recipe that uses the selected product from the cooking recipe storage unit that stores the product information used for cooking and the cooking recipe in association with each other.
Further provided with a deficient product determination unit for determining a deficient product that is not used for cooking by comparing the product used in the cooking recipe acquired by the cooking recipe acquisition unit with the selected product.
The recommended information specifying unit extracts the deficient product information related to the deficient product from the plurality of product information, and specifies the cooking recipe acquired by the cooking recipe acquisition unit and the deficient product information as the recommended information. The recommended information specifying device according to claim 1. When the predetermined condition is satisfied, the cooking recipe acquisition unit uses the cooking recipe that uses the product included in the purchase target information acquired by the purchase target information acquisition unit by the time the predetermined condition is satisfied. Obtained from the storage
The recommended information identification unit according to claim 2, wherein the recommended information specifying unit specifies the cooking recipe acquired by the cooking recipe acquisition unit and the insufficient product information as the recommended information after the determination by the insufficient product determination unit. apparatus. The predetermined condition is that the selection time from the selection of the previous product to the selection of the next product is longer than the predetermined set time, or the number of products of the selected product is predetermined. The recommended information specifying device according to claim 3, wherein the set number has been reached. The predetermined condition is that the selection time from the selection of the previous product to the selection of the next product is longer than the predetermined set time, or the number of products of the selected product is predetermined. It is either that the set number has been reached,
The recommended information specifying unit is described in claim 1, wherein the recommended information is specified from the plurality of product information based on the purchase target information acquired by the purchase target information acquisition unit until the predetermined condition is satisfied. Recommended information identification device. The recommended information specifying device according to any one of claims 1 to 5, further comprising a recommended information output unit that outputs the recommended information specified by the recommended information specifying unit to the terminal device. A purchase target information acquisition unit that acquires purchase target information for each product selected as a purchase target of the user in the store from a terminal device used by the user in the store.
When a predetermined condition is satisfied for the selection of the product, the user is stored in the product information storage unit in which a plurality of product information related to the plurality of products provided at the store is stored based on the purchase target information. Recommended information identification department that identifies recommended information including recommended products according to
A recommended information specifying system including a recommended information output unit that outputs the recommended information specified by the recommended information specifying unit to the terminal device. The purchase target information acquisition step of acquiring the purchase target information for each of the products selected as the purchase target of the user in the store from the terminal device used by the user in the store, and the purchase target information acquisition step.
When a predetermined condition predetermined for the selection of the product is satisfied, the product information storage unit stores a plurality of product information reports relating to the plurality of products provided at the store based on the purchase target information. A recommended information identification step that identifies recommended information, including recommended products for each user, and a recommended information identification method that is performed by one or more processors. A program for causing one or more processors to execute each step of the recommended information identification method according to claim 8. A terminal device that a user uses in a store when purchasing a product.
A transmission processing unit that transmits purchase target information for each product selected as a purchase target by the user at the store to the recommended information specifying device according to any one of claims 1 to 6.
A terminal device including a display processing unit that displays the recommended information specified in the recommended information specifying device that has acquired the purchase target information from the terminal device on a predetermined display unit. This method is applied to the terminal device that the user uses in the store when purchasing the product.
A transmission step of transmitting purchase target information for each product selected as a purchase target of the user at the store to the recommended information specifying device according to any one of claims 1 to 6.
A method in which one or a plurality of processors execute a display step of displaying the recommended information specified in the recommended information specifying device, which has acquired the purchase target information from the terminal device, on a predetermined display unit. A program for causing one or more processors to perform each step of the method according to claim 11.

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