JP2020067986A - Determination device, determination method, and determination program - Google Patents

Abstract

To provide a determination device, a determination method, and a determination program, capable of determining whether a user carrying a terminal device has become interested in a prescribed object.SOLUTION: A determination device according to an embodiment comprises an acquisition unit and a determination unit. The acquisition unit acquires sensor information detected by a sensor mounted on a terminal device carried by a user. The determination unit determines an interest degree of the user to the prescribed object on the basis of the sensor information acquired by the acquisition unit.SELECTED DRAWING: Figure 1

Description

  The disclosed embodiments relate to a determination device, a determination method, and a determination program.

  2. Description of the Related Art Conventionally, there is known a technique of detecting a visit state or a usage state of a store by a user and providing a predetermined service based on the detection result. As an example of such a technique, there is known a technique of giving a privilege to a customer when the customer visits the store.

JP, 2002-279285, A

  However, just because a customer visits a store does not mean that the customer is interested in a predetermined target object such as a product handled in the store, so the awarding of the privilege becomes useless. There is a fear.

  One aspect of the embodiment has been made in view of the above, and a determination device, a determination method, and a determination device that can determine whether or not a user carrying a terminal device has an interest in a predetermined target object. The purpose is to provide the program.

  The determination device according to one aspect of the embodiment includes an acquisition unit and a determination unit. The acquisition unit acquires sensor information detected by a sensor mounted on a terminal device carried by a user. The determination unit determines the degree of interest of the user with respect to a predetermined target object based on the sensor information acquired by the acquisition unit.

  According to the determination device, the determination method, and the determination program according to one aspect of the embodiment, it is possible to determine whether the user carrying the terminal device has an interest in a predetermined target object.

FIG. 1 is an explanatory diagram showing an outline of the determination method according to the embodiment. FIG. 2 is a block diagram showing an example of the configuration of the determination device according to the embodiment. FIG. 3A is an explanatory diagram of a learning model creation procedure according to the embodiment. FIG. 3B is an explanatory diagram of a learning model creation procedure according to the embodiment. FIG. 3C is an explanatory diagram of a learning model creation procedure according to the embodiment. FIG. 3D is an explanatory diagram of a learning model creation procedure according to the embodiment. FIG. 4 is an explanatory diagram illustrating an example of the provision list according to the embodiment. FIG. 5 is a flowchart illustrating an example of processing executed by the control unit of the determination device according to the embodiment. FIG. 6 is a hardware configuration diagram illustrating an example of a computer that realizes the determination device according to the embodiment.

  Hereinafter, modes (hereinafter, referred to as “embodiments”) for carrying out the determination device, the determination method, and the determination program according to the present application will be described in detail with reference to the drawings. Note that the determination device, the determination method, and the determination program according to the present application are not limited to this embodiment. Further, the respective embodiments can be appropriately combined within the range in which the processing content is not inconsistent. Also, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicated description will be omitted.

[1. Overview of judgment method]
FIG. 1 is an explanatory diagram showing an outline of the determination method according to the embodiment. As shown in FIG. 1, for example, the user U of the terminal device 10-1 stops while taking a note while walking in front of a display shelf 100 on which products are displayed in a store that sells home electric appliances. You may leave the store after looking at the personal computer 11.

  It is possible that the user U who took such an action hesitated to purchase the notebook computer 11 at the store, and eventually gave up buying the notebook computer 11 and left the store. Then, such a user may purchase the notebook computer 11 at a price lower than the selling price at the store later by using, for example, a shopping site on the Internet.

  In this case, the store side misses the opportunity for the user U to purchase the notebook computer 11 at the store, and the sales of the product are reduced. At this time, for example, if it is possible to provide the store with information that the user U was interested in the notebook computer 11 in the store, the store side prompts the user U to purchase the notebook computer 11. It is possible to deal with it and increase sales.

  Therefore, the determination device 1 according to the embodiment acquires the sensor information detected by the sensor mounted on the terminal device 10-1 from the terminal device 10-1 carried by the user U moving in the store (step S1). ).

  Specifically, for example, a terminal device 10-1 such as a smartphone carried by the user U is equipped with a GPS (Global Positioning System) sensor in recent years. The GPS sensor is a sensor that measures the position of the user U based on radio waves received from GPS satellites.

  Therefore, the determination device 1 can determine the position of the user U in the store by acquiring the sensor information from the GPS sensor of the terminal device 10-1, and the position of the user and the display place of the product in the store. From this, the product in which the user U is interested can be specified.

  For example, the determination device 1 determines that the user U was interested in the notebook computer 11 when the user U stopped in front of the notebook computer 11 in the store and did not leave the notebook computer 11 for a predetermined time or longer. be able to.

  Further, for example, the determination device 1 can determine that the user U is interested in the notebook computer 11 even when the user U moves in the store and stops at the notebook computer 11 multiple times. .

  In this way, when the user U determines that the user U is interested in the notebook computer 11 based on the sensor information acquired from the terminal device 10-1 (step S2), the determination device 1 indicates the degree of interest of the user U in the notebook computer 11. Information including the determination result is provided to the store device 110 (step S3).

  The store device 110 is a device managed by a store where the user U comes to the store and is interested in the notebook computer 11. When the store apparatus 110 receives the provision of the information including the determination result of the degree of interest to the notebook computer 11 of the user U from the determination apparatus 1, the store apparatus 110 delivers the information regarding the notebook computer 11 to the terminal device 10-1 of the user U. (Step S4).

  For example, the store apparatus 110 can deliver to the terminal device 10-1 of the user U a retargeting advertisement such as coupon content that enables the notebook computer 11 to be purchased at a lower price than other stores. As a result, the store can increase the willingness of the user U to purchase the notebook computer 11.

  As described above, according to the determination device 1, when the user U determines that the user is interested in the notebook computer 11 based on the sensor information acquired from the terminal device 10-1, the store side including the determination result is useful information. It can be provided to the store device 110.

  In addition, the recent terminal device 10-1 is equipped with a motion sensor. The motion sensor includes an acceleration sensor, a gyro sensor, and the like, and for example, detects the orientation of the screen of the terminal device 10-1 and measures the position of the user U who walks by PDR (Pedestrian Dead Reckoning). It has been the main application to date.

  Since the motion sensor includes an acceleration sensor, a gyro sensor, and the like, for example, it is possible to detect even a slight vibration or behavior when the user U stops, turns around, crouches, or talks with a person with him / her. it can.

  Therefore, the determination device 1 acquires the sensor information detected by the motion sensor from the terminal device 10-1, and based on the acquired sensor information, the degree of interest of the user U with respect to the specific product displayed in the store. Can also be determined.

  Thereby, the determination device 1 can more accurately determine the degree of interest of the user U with respect to the specific product. In such a case, the determination device 1 uses the learning model in which the sensor information corresponding to the characteristic behavior taken by another user in the vicinity of the particular product of interest is machine-learned in advance, and the user U with respect to the particular product. Determine the degree of interest in. An example of the learning model creation procedure will be described later with reference to FIGS. 3A to 3D.

[2. Configuration of determination device 1]
Next, an example of the configuration of the determination device 1 according to the embodiment will be described with reference to FIG. FIG. 2 is a block diagram showing an example of the configuration of the determination device 1 according to the embodiment. As shown in FIG. 2, the determination device 1 includes a communication unit 2, a storage unit 3, and a control unit 4.

(About communication unit 2)
The communication unit 2 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 2 is wirelessly connected to, for example, a communication network N such as the Internet, and through the communication network N, a plurality of terminal devices 10-1 to 10-n (n is a natural number of 2 or more), a store. Information is transmitted and received between the device 110 and the advertisement distribution device 111.

  In the following description, the term “terminal device 10” is used when referring to any device among the plurality of terminal devices 10-1 to 10-n. Each terminal device 10 is, for example, a smartphone or a tablet terminal carried by a user.

  Each terminal device 10 includes a GPS sensor 101 and a motion sensor 102. The motion sensor 102 includes, for example, an acceleration sensor, a gyro sensor, a step sensor, and a biological sensor.

  The acceleration sensor is a sensor that detects the acceleration of the terminal device 10. The gyro sensor is a sensor that detects the posture, angular velocity, and the like of the terminal device 10. The step count sensor is a sensor that counts the number of steps taken by the user of the terminal device 10.

  The biometric sensor is a sensor that detects the heart rate, body temperature, and the like of the user of the terminal device 10. In FIG. 2, the components other than the GPS sensor 101 and the motion sensor 102 included in the terminal device 10 are not shown.

  The store device 110 is a device managed by an actual store that actually displays and sells products. The advertisement distribution device 111 is a device that distributes various advertisement contents to the terminal device 10 and the like.

(About storage unit 3)
The storage unit 3 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. The storage unit 3 has display place information 31, a learning model 32, and a provision list 33.

  The display location information 31 is information in which the display location of a specific product in the store is associated with the identification information of the product displayed at that location. The display location information 31 may include display locations of all the products in the store and identification information of the products displayed at the location. The provision list 33 is a list of information provided from the determination device 1 to the store device 110 and the advertisement distribution device 111. An example of the provision list 33 will be described later with reference to FIG.

  When the position of the user acquired from the terminal device 10 and the sensor information detected by the motion sensor 102 are input, the learning model 32 determines whether or not the user is interested in a specific product, and further determines a specific product. Outputs the determination result of whether or not he / she was confused about purchasing.

  The learning model 32 is created by preliminarily machine learning the sensor information corresponding to the characteristic behavior of the user in the vicinity of the particular product of interest. Here, an example of a procedure for creating the learning model 32 will be described with reference to FIGS. 3A to 3D.

(Example of procedure for creating learning model 32)
3A to 3D are explanatory diagrams of a learning model creation procedure according to the embodiment. As shown in FIG. 3A, when creating the learning model 32, the correct answer sensor information D is prepared in advance. At this time, as the correct answer sensor information D, a large number of sensor information acquired from the terminal device 10 of the user who is interested in the specific product and the terminal device 10 of the user who is unsure about purchasing the specific product. Prepare a lot of sensor information. Further, a large number of sensor information acquired from the terminal device 10 of a user who is not interested in a specific product is prepared.

  For example, when the learning model 32 used to determine the degree of interest of the customer (user of the terminal device 10) with respect to the notebook computer 11 is created, a user who passes by the notebook computer 11 is photographed by a camera.

  Then, from the images taken by the camera, a user who is interested in the notebook computer 11, a user who is interested in the notebook computer 11 and is unsure of purchase, and a user who is not interested in the notebook computer 11 are specified. . Then, the position of each user and the sensor information detected by the motion sensor 102 are collected from the terminal device 10 of each user.

  The sensor information # 1 to # 5 illustrated in FIG. 3A is sensor information acquired from the terminal device 10 of a user who is interested in a specific product. Further, among the sensor information # 1 to # 5, the sensor information # 4 and # 5 are sensor information acquired from the terminal device 10 of the user who is unsure about purchasing a specific product. Further, the sensor information # 6 is sensor information acquired from the terminal device 10 of a user who is not interested in a specific product.

  The sensor information # 1 is, for example, sensor information acquired from the terminal device 10 of the user who stopped in front of the notebook computer 11 and gazed at the notebook computer 11. The sensor information # 2 is, for example, sensor information acquired from the terminal device 10 of a user who walks straight toward the notebook computer 11.

  The sensor information # 3 is, for example, sensor information acquired from the terminal device 10 of the user who walked while searching for the notebook computer 11. The sensor information # 4 is, for example, sensor information acquired from the terminal device 10 of the user who has a conversation while looking at the notebook computer 11.

  The sensor information # 5 is, for example, sensor information acquired from the terminal device 10 of the user who repeatedly operated the notebook computer 11 as a trial. The sensor information # 6 is, for example, sensor information acquired from the terminal device 10 of the user who has passed through without looking at the notebook computer 11. It should be noted that the sensor information # 1 to the sensor information # 6 include the location where each is acquired and the location such as the route traveled by the user.

  After that, as the correct answer to the collected sensor information # 1 to # 6, etc., any one of the information that the user is interested in the notebook computer 11, is interested and hesitated to purchase, or is not interested Is input to the computer PC having the function of creating the learning model 32. The computer PC creates the learning model 32 by machine learning by FM (Factorization Machines), for example.

  For example, as shown in FIG. 3B, the computer PC plots the input sensor information such as sensor information # 1 to # 6 on a predetermined coordinate plane M. In FIG. 3B, the sensor information to which the correct answer that the user is interested is added is shown by a white dot, and the sensor information to which the correct answer that the user is interested and hesitated to buy is added is shown by a white triangle. The sensor information to which the correct answer that the user was not interested is given is indicated by a black dot.

  Subsequently, as shown in FIG. 3C, the computer PC provides a sensor information group indicated by a white dot or a white triangle to which the correct answer that the user is interested and a correct answer that the user is not interested. A boundary line L1 for classifying the sensor information group indicated by the black dots is set on the coordinate plane M.

  Further, the computer PC has a sensor information group indicated by white dots to which the correct answer that the user is interested is added, and a sensor information group indicated by white triangles to which the correct answer that the user is interested and lost the purchase is added. Boundary line L2 for classifying is set on coordinate plane M.

  Then, as shown in FIG. 3D, the computer PC sets an area above the boundary line L1 in the coordinate plane M as an interesting area, and an area below the boundary line L1 as a non-interesting area. Of these, the learning model 32 is created in which the area on the left side of the boundary line L2 is the area where the purchase is lost.

  The learning model 32 plots the sensor information D1 including the position of the user on the coordinate plane M when the position and the sensor information of the user acquired from the terminal device 10 of a certain user are input, for example.

  At this time, as shown in FIG. 3D, when the area in which the sensor information D1 is plotted is an area in which purchase is uncertain, the learning model 32 indicates that the user of the terminal device 10 who has acquired the sensor information D1 is interested in the notebook computer 11. The determination result that the user has the item and has lost the purchase is output.

(About control unit 4)
Returning to FIG. 2, the control unit 4 will be described. The control unit 4 is a controller, and is, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like, which stores various programs (an example of a determination program) stored in a storage device inside the determination device 1. (Corresponding) is executed by using the RAM as a work area. The control unit 4 is, for example, a controller and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

  As shown in FIG. 2, the control unit 4 has an acquisition unit 41, a determination unit 42, and a provision unit 43, and realizes or executes the functions and actions of information processing described below. The internal configuration of the control unit 4 is not limited to the configuration shown in FIG. 2, and may be another configuration as long as it is a configuration for performing information processing described later.

(About acquisition unit 41)
The acquisition unit 41 acquires, from the terminal device 10, sensor information detected by the GPS sensor 101 and sensor information detected by the motion sensor 102. At this time, the acquisition unit 41 acquires the position of the user from the GPS sensor 101 when the position of the user is measured by the GPS sensor 101 of the terminal device 10.

  However, in the terminal device 10, there are cases where the position of the user cannot be measured by the GPS sensor 101. For example, when the terminal device 10 is located in an underground store facility or the like, the terminal device 10 cannot receive radio waves from GPS satellites and therefore cannot perform positioning by the GPS sensor 101.

  In such a case, the acquisition unit 41 can measure the position of the user by PDR, for example. When the acquisition unit 41 cannot receive the radio waves from the GPS satellites, the acquisition unit 41 is based on the position of the user finally measured by the GPS sensor 101 and the acceleration, angular velocity, and the number of steps of the user detected by the motion sensor 102 thereafter. Get the estimated user location. Then, the acquisition unit 41 sequentially outputs the acquired positions and sensor information of the users of the plurality of terminal devices 10 to the determination unit 42.

  Further, if the acquisition unit 41 can receive radio waves from a plurality of WiFi access points when it cannot receive radio waves from GPS satellites, the acquisition unit 41 determines the user's position by three-point positioning because of the difference in the reception intensity of the received radio waves from each WiFi access point. You can also get the position.

  Further, when the radio wave from the GPS satellite cannot be received, the acquisition unit 41 can also acquire the position of the user based on, for example, a signal transmitted from a beacon transmitter installed in the store.

(About the determination unit 42)
The determination unit 42 determines whether or not the user is interested in a specific product based on the position of each user sequentially input from the acquisition unit 41 and the display location information 31 stored in the storage unit 3, and It is determined whether or not the purchase of the item is lost.

  Furthermore, the determination unit 42 inputs the position of each user and the sensor information detected by the motion sensor 102, which are sequentially input from the acquisition unit 41, to the learning model 32. Then, the determination unit 42 determines, based on the output of the learning model 32, whether or not the user was interested in a specific product and whether he / she was hesitant to purchase the specific product.

  Then, the determination unit 42 ANDs or ORs the determination result based on the position and display location information 31 of each user with the determination result based on the position of each user, the sensor information detected by the motion sensor 102, and the learning model 32. Then, the user who is confused about purchasing a specific product is determined.

  Then, the determination unit 42 registers the determination result in the provision list 33. As a result, for example, as shown in FIG. 4, in the provision list 33, for example, the user ID of a user who is unsure about purchasing a laptop computer manufactured by A company and the date and time of coming to the store, and the purchase of a tablet terminal manufactured by B company. Information such as the user ID of the lost user and the date and time of visit to the store is registered in a list format.

(About the providing section 43)
The provision unit 43 provides the information included in the provision list 33 to the store apparatus 110 and the advertisement distribution apparatus 111. As a result, the store device 110 or the advertisement distribution device 111 that has been provided with the information from the providing unit 43 provides the user with a lower price than other stores, for example, to a user who did not purchase a particular product due to hesitation. It is possible to deliver retargeting advertisements such as coupon contents that can be purchased at. As a result, it is possible to increase the user's willingness to purchase a specific product for which purchase has been lost.

[3. Processing procedure]
Next, with reference to FIG. 5, an example of a process executed by the control unit 4 of the determination device 1 according to the embodiment will be described. FIG. 5 is a flowchart showing an example of processing executed by the control unit 4 of the determination device 1 according to the embodiment.

  As shown in FIG. 5, the control unit 4 first acquires sensor information from the user's terminal device 10 (step S101). Subsequently, the control unit 4 determines the degree of interest of the user with respect to the specific product based on the acquired sensor information (step S102).

  Further, the control unit 4 determines whether or not the user is uncertain about purchasing a specific product (step S103). Then, the control unit 4 provides the store device 110 and the advertisement distribution device 111 with information including the determination result of the degree of interest of the user with respect to the specific product and the determination result of whether or not the user is uncertain about purchasing the specific product. It is provided (step S104), and the process ends.

[4. Modification example)
The determination device 1 described above may be implemented in various different forms other than the above-described embodiment. Therefore, a modification of the determination device 1 will be described below. In the above-described embodiment, the determination device 1 allows the user to purchase a specific product by the determination process based on the position of the user and the determination process based on the position of the user, the sensor information of the motion sensor 102, and the learning model 32. It was determined whether or not he / she was lost, but this is an example.

  The determination device 1 performs any one of a determination process based on the position of the user and a determination process based on the position of the user, the sensor information of the motion sensor 102, and the learning model 32, so that the user can identify the specific position. It may be determined whether or not the purchase of the product is lost.

  Further, in the above-described embodiment, the case where the determination device 1 provides the provision list 33 to the store device 110 and the advertisement distribution device 111 as useful information has been described, but it is useful based on the provision list 33 to the terminal device 10. You may provide information.

  For example, when the determination device 1 is affiliated with the store in the advertisement distribution business, the determination device 1 directly distributes the retargeting advertisement or the like relating to the specific product that the purchaser is uncertain to the terminal device 10 based on the information in the provision list 33. Good.

  As a result, the determination device 1 can more quickly deliver the retargeting advertisement to the terminal device 10 as compared with the case where the provision list 33 is provided to the store device 110 and the advertisement delivery device 111.

  Further, in the above-described embodiment, the determination unit 42 determines whether or not the user is confused about the purchase of the specific product, but it is determined whether or not the user is confused about the use of the specific service provided in the actual store. You can also do it.

  Further, in the above-described embodiment, the case where the control unit 4 of the determination device 1 includes the provision unit 43 has been described, but the control unit 4 is not limited to the provision unit 43 as long as the control unit 4 includes at least the acquisition unit 41 and the determination unit 42. Does not have to be provided.

  In the case of such a configuration, the determination device 1 transmits the determination result by the determination unit 42 to, for example, the provision device including the provision unit 43, and the determination device transmits the determination result to the store device 110, the advertisement distribution device 111, the terminal device 10, and the like. Information is provided according to the determination result of 42.

[5. Hardware configuration]
The determination device 1 according to the above-described embodiment is realized by, for example, a computer 1000 configured as shown in FIG. FIG. 6 is a hardware configuration diagram illustrating an example of a computer 1000 that realizes the functions of the determination device 1. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

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

  The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. Communication I / F (interface) 1500 receives data from another device via communication network N, sends the data to CPU 1100, and transmits the data generated by CPU 1100 to the other device via communication network N.

  The CPU 1100 controls output devices such as a display and a printer and input devices such as a keyboard and a mouse via the input / output I / F 1600. The CPU 1100 acquires data from the input device via the input / output I / F 1600. The CPU 1100 also outputs the data generated via the input / output interface 1600 to the output device. In FIG. 6, the input device and the output device are collectively shown as an input / output device.

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

  For example, when the computer 1000 functions as the determination device 1 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 4 by executing the program loaded on the RAM 1200. Further, the HDD 1400 stores the data in the storage unit 3. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via the communication network N.

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

  Further, each component of each device shown in the drawings is functionally conceptual, and does not necessarily have to be physically configured as shown. That is, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part of the device may be functionally or physically distributed / arranged in arbitrary units according to various loads and usage conditions. It can be integrated and configured. For example, the acquisition unit 41 and the determination unit 42 illustrated in FIG. 2 may be integrated. Further, for example, the information stored in the storage unit 3 may be stored in a predetermined storage device provided outside via the communication network N.

  Further, in the above-described embodiment, the determination device 1, for example, based on the acquisition process of acquiring the sensor information detected by the sensor mounted on the terminal device carried by the user, and the sensor information acquired by the acquisition process, An example has been shown in which the determination process of determining the degree of interest of the user with respect to a predetermined object and the providing process of providing information based on the determination result of the determination process are performed.

  However, the determination device 1 described above may be separated into an acquisition device that performs the acquisition process, a determination device that performs the determination process, and a provision device that performs the provision process. In this case, the acquisition device has at least the acquisition unit 41. The determination device has at least a determination unit 42. The providing device includes at least the providing unit 43. Then, the processing by the determination device 1 described above is realized by an information providing system including the acquisition device, the determination device, and the providing device.

  Further, the above-described embodiments and modified examples can be appropriately combined within a range in which the processing content is not inconsistent.

[7. effect〕
As described above, the determination device 1 according to the embodiment includes the acquisition unit 41 and the determination unit 42. The acquisition unit 41 acquires sensor information detected by a sensor mounted on the terminal device 10 carried by the user. The determination unit 42 determines the degree of interest of the user with respect to a predetermined target object based on the sensor information acquired by the acquisition unit 41. Thereby, the determination device 1 can determine whether or not the user carrying the terminal device 10 has an interest in a predetermined target object.

  The determination device 1 further includes a providing unit 43. The providing unit 43 provides information based on the determination result of the determining unit 42. Thereby, the determination device 1 can provide useful information according to, for example, the degree of interest of the user with respect to a predetermined target object.

  In addition, the determination unit 42 determines whether the user is confused about purchasing a specific product or using a specific service based on the sensor information acquired by the acquisition unit 41. Thereby, the determination device 1 can provide useful information regarding, for example, a specific product that the user is confused about purchasing or a specific service that the user is confused about using.

  Further, the providing unit 43 provides information including the determination result of the determining unit 42 to the actual store that provides the specific product or the specific service. Thereby, for example, a store that sells a specific product can actively perform a sales promotion action for a user who is uncertain about purchasing the specific product.

  Further, the providing unit 43 provides the advertisement distribution device 111 that distributes the advertising content to the terminal device 10 with the information including the determination result by the determination unit 42. Accordingly, the advertisement distribution device 111 can increase the user's willingness to purchase the specific product by, for example, distributing the advertising content related to the specific product that the user is unsure of purchasing to the user's terminal device 10.

  Further, the providing unit 43 provides the user, who is determined by the determination unit 42 that he or she is uncertain about purchasing a specific product or using a specific service, with information about the specific product. Thereby, the determination device 1 can increase the user's willingness to purchase a specific product.

  Further, the acquisition unit 41 acquires the position of the user included in the sensor information, and the determination unit 42 determines the degree of interest of the user with respect to a predetermined target object based on the position of the user acquired by the acquisition unit 41. . Thereby, the determination device 1 can accurately determine the degree of interest of the user with respect to the predetermined target object.

  The acquisition unit 41 acquires sensor information detected by a motion sensor included in the sensor, and the determination unit 42 determines a predetermined target based on the sensor information detected by the motion sensor acquired by the acquisition unit 41. Determining the user's degree of interest in an object. Thereby, the determination device 1 can more accurately determine the degree of interest of the user with respect to the predetermined target object.

  As described above, the embodiments of the present application have been described in detail with reference to the drawings, but this is an example, and various modifications and improvements are made based on the knowledge of those skilled in the art, including the modes described in the section of the disclosure of the invention. The present invention can be carried out in other forms described above.

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

DESCRIPTION OF SYMBOLS 1 Judgment device 2 Communication part 3 Storage part 31 Display place information 32 Learning model 33 Providing list 4 Control part 41 Acquisition part 42 Judgment part 43 Providing part 10,10-1-10-n Terminal device 110 Store device 111 Advertising distribution device

Claims (10)

An acquisition unit for acquiring sensor information detected by a sensor mounted on a terminal device carried by a user,
A determination unit that determines the degree of interest of the user with respect to a predetermined object based on the sensor information acquired by the acquisition unit. The determination device according to claim 1, further comprising: a providing unit that provides information based on a determination result by the determination unit. The determination unit,
The determination device according to claim 2, wherein it is determined whether the user is uncertain about purchasing a specific product or using a specific service based on the sensor information acquired by the acquisition unit. . The providing unit is
The determination device according to claim 3, wherein information including the determination result by the determination unit is provided to an actual store that provides the specific product or the specific service. The providing unit is
The determination device according to claim 3 or 4, wherein information including the determination result by the determination unit is provided to an advertisement distribution device that distributes the advertising content to the terminal device. The providing unit is
The information regarding the specific product or the specific service is provided to the user determined by the determination unit to be uncertain about the purchase of the specific product or the use of the specific service. The determination device according to any one of 5. The acquisition unit is
Obtaining the position of the user included in the sensor information,
The determination unit,
The determination apparatus according to any one of claims 1 to 6, wherein the degree of interest is determined based on the position of the user acquired by the acquisition unit. The acquisition unit is
Obtaining sensor information detected by the motion sensor included in the sensor,
The determination unit,
The determination device according to claim 7, wherein the degree of interest is determined based on sensor information detected by the motion sensor acquired by the acquisition unit. A determination method executed by a computer,
An acquisition step of acquiring sensor information detected by a sensor mounted on a terminal device carried by a user,
And a determination step of determining the degree of interest of the user with respect to a predetermined object based on the sensor information acquired in the acquisition step. An acquisition procedure for acquiring sensor information detected by a sensor mounted on a terminal device carried by a user,
And a determination procedure for determining the degree of interest of the user with respect to a predetermined object based on the sensor information acquired by the acquisition procedure.

Images