Category classification program, category classification device, category classification method, and recording medium

Abstract

This disclosure provides a category classification program capable of classifying categories into appropriately formed groups. [Solution] The category classification program of this disclosure includes a time acquisition procedure, a companion subject extraction procedure, a group formation procedure, an attribute information acquisition procedure, and a category classification procedure, wherein the time acquisition procedure acquires the time period when each subject was in a specific area, the companion subject extraction procedure extracts companion subjects from a plurality of subjects whose time periods are the same, the group formation procedure forms a group composed of the companion subjects for each specific area, the attribute information acquisition procedure acquires attribute information relating to the attributes of the subjects constituting the group, and the category classification procedure classifies the group into a predetermined category based on the attribute information.

Description

Technical Field

[0001] The present disclosure relates to a category classification program, a category classification apparatus, a category classification method, and a recording medium.

Background Art

[0002] Patent Document 1 discloses an information providing apparatus that determines a group attribute of a group based on attributes of persons belonging to the group and the number of persons in the group, and outputs provision information corresponding to the group attribute.

Prior Art Literature

Patent Literature

[0003]

Patent Document 1

Summary of the Invention

Problem to be Solved by the Invention

[0004] Determination of group attributes as in the invention according to Patent Document 1 requires appropriate group formation as a prerequisite.

[0005] Accordingly, an object of the present disclosure is to provide a category classification program, a category classification apparatus, a category classification method, and a recording medium that are capable of classifying categories for appropriately formed groups.

Means for Solving the Problem

[0006] In order to achieve the above object, the category classification program of the present disclosure: comprises a time acquisition procedure, an accompanying subject extraction procedure, a group formation procedure, an attribute information acquisition procedure, and a category classification procedure, the time acquisition procedure acquires, for each subject, a period during which the subject stayed in a specific area, The procedure for selecting accompanying persons involves selecting from multiple persons that are in the same time period as accompanying persons, The group formation procedure involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons who constitute the group, The aforementioned category classification procedure classifies the group into a predetermined category based on the attribute information. This is a program that causes a computer to execute each of the aforementioned steps.

[0007] The category classification device disclosed herein is It includes a timing acquisition unit, a companion target extraction unit, a group formation unit, an attribute information acquisition unit, and a category classification unit, The aforementioned time acquisition unit acquires the time period during which each subject was in a specific area, The aforementioned accompanying person extraction unit extracts from a group of aforementioned persons the persons who are in the same time period as accompanying persons, The group formation unit forms groups composed of the accompanying persons for each specific area, The attribute information acquisition unit acquires attribute information relating to the attributes of the subject persons constituting the group, The category classification unit classifies the group into a predetermined category based on the attribute information. It is a device.

[0008] The method of categorizing in this disclosure is: This includes a timing acquisition process, a process for selecting accompanying persons, a group formation process, an attribute information acquisition process, and a category classification process. The aforementioned time acquisition process acquires the time period during which each subject was in a specific area, The aforementioned process of selecting accompanying persons involves selecting from a group of persons that are in the same time period as accompanying persons, The group formation step involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition step involves acquiring attribute information relating to the attributes of the subject persons constituting the group, The category classification step involves classifying the group into a predetermined category based on the attribute information. This method involves each of the aforementioned steps being performed by a computer.

[0009] The recording medium disclosed herein is This includes procedures for obtaining timing, extracting accompanying persons, forming groups, obtaining attribute information, and categorizing. The aforementioned procedure for obtaining the time period involves obtaining the time period during which each subject was in a specific area, The procedure for selecting accompanying persons involves selecting from multiple persons that are in the same time period as accompanying persons, The group formation procedure involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons who constitute the group, The aforementioned category classification procedure classifies the group into a predetermined category based on the attribute information. This is a computer-readable recording medium on which a program is recorded that causes a computer to execute each of the aforementioned procedures. [Effects of the Invention]

[0010] According to this disclosure, categories can be classified for appropriately formed groups. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 is a block diagram showing the configuration of an example of a category classification device according to this disclosure. [Figure 2] Figure 2 is a block diagram showing an example of the hardware configuration of the category classification device of this disclosure. [Figure 3] Figure 3 is a flowchart showing an example of the procedure using the category classification program of this disclosure. [Figure 4] FIG. 4 is a schematic diagram showing an example of the category classification according to the present disclosure. [Figure 5] FIG. 5 is a block diagram showing the configuration of another example of the category classification apparatus according to the present disclosure. [Figure 6] FIG. 6 is a flowchart showing another example of a procedure by the category classification program according to the present disclosure. [Figure 7] FIG. 7 is a block diagram showing the configuration of another example of the category classification apparatus according to the present disclosure. [Figure 8] FIG. 8 is a flowchart showing another example of a procedure by the category classification program according to the present disclosure. [Figure 9] FIG. 9 is a block diagram showing the configuration of another example of the category classification apparatus according to the present disclosure. [Figure 10] FIG. 10 is a flowchart showing another example of a procedure by the category classification program according to the present disclosure. [Figure 11] FIG. 11 is a block diagram showing the configuration of another example of the category classification apparatus according to the present disclosure. [Figure 12] FIG. 12 is a flowchart showing another example of a procedure by the category classification program according to the present disclosure. DETAILED DESCRIPTION OF EMBODIMENTS

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments. In the following drawings, the same reference numerals are assigned to the same parts. In addition, the descriptions of each embodiment can be incorporated into each other unless otherwise stated, and the configurations of each embodiment can be combined unless otherwise stated. In the present disclosure, each drawing may be applicable to one or more embodiments.

[0013] [Embodiment 1] The category classification program described herein is a program that causes a computer to execute a timing acquisition procedure, a procedure for selecting accompanying persons, a group formation procedure, an attribute information acquisition procedure, and a category classification procedure. The category classification program described herein can also be described as a program that causes a computer to function as the timing acquisition procedure, the procedure for selecting accompanying persons, the group formation procedure, the attribute information acquisition procedure, and the category classification procedure. Furthermore, the category classification program described herein can also be described as a program that causes a computer to execute each step of the category classification method described later.

[0014] The aforementioned time acquisition procedure acquires the time period during which each subject was in a specific area; the accompanying subject extraction procedure extracts subjects who were in the same time period as the accompanying subjects from among multiple subjects; the group formation procedure forms groups composed of the accompanying subjects for each specific area; the attribute information acquisition procedure acquires attribute information regarding the attributes of the subjects constituting the group; and the category classification procedure classifies the group into a predetermined category based on the attribute information.

[0015] Each of the aforementioned steps can be reinterpreted, for example, by substituting "step" with "process." The category classification program of this disclosure may also be recorded on, for example, a computer-readable storage medium. The storage medium is, for example, a non-transitory computer-readable storage medium. The storage medium is not particularly limited and includes, for example, random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (e.g., SSD (Solid State Drive), USB flash memory, SD / SDHC card, etc.), optical disc (e.g., CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy disk (FD), etc. The category classification program of this disclosure (for example, also called a programming product or program product) may also be delivered, for example, from an external computer. The "delivery" may be, for example, delivery via a communication network or delivery via a wired device. The category classification program of this disclosure may be installed and run on the delivered device, or it may be run without being installed. An information processing device capable of executing the category classification program of this disclosure may be, for example, the category classification device of this disclosure.

[0016] Next, an example of the configuration of the category classification device of this disclosure will be described with reference to Figure 1. Figure 1 is a block diagram showing an example of the configuration of the category classification device 10 of this disclosure (hereinafter also referred to as "the device 10"). As shown in Figure 1, the device 10 includes a time acquisition unit 11, a companion subject extraction unit 12, a group formation unit 13, an attribute information acquisition unit 14, and a category classification unit 15. The device 10 may also include, for example, an input unit, an output unit, a display unit, and / or a storage unit, although these are not shown. The time acquisition unit 11, the companion subject extraction unit 12, the group formation unit 13, the attribute information acquisition unit 14, and the category classification unit 15 can each execute, for example, the time acquisition procedure, the companion subject extraction procedure, the group formation procedure, the attribute information acquisition procedure, and the category classification procedure in the group formation program of this disclosure.

[0017] The device 10 may be, for example, a single device including the aforementioned parts, or it may be a device in which each of the aforementioned parts can be connected via a communication network. Furthermore, the device 10 can be connected to an external device described later via the communication network. The communication network is not particularly limited and can use a known network, for example, it may be wired or wireless. Examples of the communication network include the Internet, WWW (World Wide Web), telephone lines, LAN (Local Area Network), SAN (Storage Area Network), DTN (Delay Tolerant Networking), LPWA (Low Power Wide Area), L5G (Local 5G), etc. Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), Local 5G, LPWA, etc. The wireless communication may be in the form of direct communication between devices (Ad Hoc communication), infrastructure communication, indirect communication via an access point, etc. The device 10 may be, for example, incorporated into a server as a system. Furthermore, the device 10 may be, for example, a personal computer (PC, e.g., desktop or notebook), smartphone, tablet terminal, etc., on which the program of this disclosure is installed. The device 10 may also be in the form of cloud computing or edge computing, for example, in which at least one of the aforementioned parts is on a server and the other aforementioned parts are on a terminal.

[0018] Figure 2 illustrates a block diagram of the hardware configuration of the device 10. The device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, memory 102, bus 103, storage device 104, input device 105, output device 106, communication device 107, etc. Each part of the device 10 is interconnected via the bus 103 through its respective interface (I / F).

[0019] The central processing unit 101 operates in coordination with other components via controllers (system controller, I / O controller, etc.) and is responsible for the overall control of the device 10. In the device 10, the central processing unit 101 executes, for example, the program of this disclosure (category classification program) and other programs, and also reads and writes various types of information. Specifically, for example, the central processing unit 101 functions as a time acquisition unit 11, a companion target extraction unit 12, a group formation unit 13, an attribute information acquisition unit 14, and a category classification unit 15. The device 10 may also include other computing devices such as a CPU, GPU (Graphics Processing Unit), APU (Accelerated Processing Unit), or a combination thereof as computing devices.

[0020] Bus 103 can also be connected to external devices, for example. Examples of such external devices include external storage devices (external databases, etc.), printers, external input devices, external display devices, and external imaging devices. The device 10 can be connected to an external network (the aforementioned communication network) via a communication device 107 connected to bus 103, for example, and can also be connected to other devices via the external network.

[0021] Memory 102 may be, for example, main memory. When the central processing unit 101 performs processing, memory 102 reads various operational programs, such as the program of this disclosure, stored in the storage device 104 (described later), and the central processing unit 101 receives data from memory 102 and executes the program. The main memory may be, for example, RAM (random access memory). Alternatively, memory 102 may be, for example, ROM (read-only memory).

[0022] The storage device 104 is also called an auxiliary storage device, for example, in relation to the main memory (primary memory). As described above, the storage device 104 stores an operating program including the program of this disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive for reading and writing to the recording medium. The recording medium is not particularly limited and may be internal or external, for example, an HD (hard disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, memory card, etc. The storage device 104 may be, for example, a hard disk drive (HDD) in which the recording medium and the drive are integrated, or a solid state drive (SSD). If the device 10 includes the storage unit, for example, the storage device 104 functions as the storage unit. The storage unit can record, for example, various types of information, which will be described later.

[0023] In this device 10, the memory 102 and storage device 104 can also store various types of information, such as log information, information obtained from an external database (not shown) or external devices, information generated by this device 10, and information used by this device 10 when executing processing. In this case, the memory 102 and storage device 104 may store, for example, the user information of this device as described above. At least some of the information may be stored on an external server other than the memory 102 and storage device 104, or it may be stored in a distributed manner across multiple terminals using blockchain technology or the like.

[0024] The device 10 further includes, for example, an input device 105 and an output device 106. The input device 105 may include, for example, a pointing device such as a touch panel, trackpad, or mouse; a keyboard; imaging means such as a camera or scanner; a card reader such as an IC card reader or magnetic card reader; an audio input means such as a microphone; and so on. The output device 106 may include, for example, a display device such as an LED display or liquid crystal display; an audio output device such as a speaker; a printer; and so on. In this embodiment 1, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated unit, such as a touch panel display.

[0025] An example of processing by the category classification program of this disclosure will be explained in more detail with reference to Figure 3. Figure 3 is a flowchart of an example of each step of the category classification program of this disclosure. The category classification program of this disclosure can be implemented, for example, using the apparatus 10 of this disclosure shown in Figure 1 or Figure 2. However, the category classification program of this disclosure is not limited to a program that uses the apparatus 10 of this disclosure.

[0026] The time acquisition unit 11 acquires the time period when each subject was in a specific area (S11, time acquisition procedure).

[0027] The aforementioned specific area is, for example, an area included in a facility. The aforementioned facility is, for example, a facility used by the aforementioned target person. The aforementioned facility may include, for example, public facilities, private facilities, etc. The aforementioned facility may include, for example, an amusement park, a movie theater, a zoo, an aquarium, a botanical garden, a museum, an art gallery, a sports field, a park, a library, a commercial facility, a gym, an event venue, an arena, a stadium, a shopping mall, a hotel, an academic conference venue, a wedding hall, etc.

[0028] The aforementioned specific area is, for example, an area used by the subject persons within the facility. The number of subject persons is, for example, two or more. The aforementioned specific area may be set appropriately depending on the type of facility. For example, if the facility is an amusement park, the aforementioned specific area may be a specific area where attractions are located, a specific area where restaurants are located, a specific area where parking is located, etc. For example, if the facility is a shopping mall, the aforementioned specific area may be a specific area where a food court is located, a specific area where each tenant is located, etc. The number of aforementioned specific areas may be, for example, one or two or more per facility.

[0029] The aforementioned specific area includes, for example, at least one of an entrance area and an exit area. The entrance area includes, for example, an entrance area relating to an entrance to the facility and an entrance area relating to an entrance to a passage within the facility. The exit area includes, for example, an exit area relating to an exit from the facility and an exit area relating to an exit from a passage within the facility. The entrance area and the exit area may be, for example, different areas or the same area. The entrance area and the exit area may be referred to as an entrance / exit area if, for example, the entrance area and the exit area are the same area. The passage within the facility may be, for example, a passage connecting the aforementioned specific areas or a passage within the aforementioned specific areas. Examples of passages within the facility include passages in a parking lot and passages leading to a VIP-only area.

[0030] The period during which the subject was in the specified area may, for example, be the period during which the subject passed through the specified area, or the period during which the subject stayed in the specified area.

[0031] The time acquisition unit 11 may acquire the time based on, for example, the time at which the subject was image-recognized.

[0032] The time acquisition unit 11 may, for example, perform the time acquisition process based on the time of image recognition as a process for acquiring the time of entry into the specific area and the time of exit from the specific area. Specifically, the time acquisition unit 11 may, for example, acquire the time when image recognition of the subject started when the subject entered the specific area as the entry time, and acquire the time when image recognition of the subject ended when the subject left the specific area as the exit time. The time acquisition unit 11 may, for example, acquire the period from the entry time to the exit time as the period when the subject was in the specific area. The time acquisition unit 11 may, for example, acquire the entry time and the exit time in image recognition performed when attribute information is acquired by the attribute information acquisition unit 14. The image recognition may take any form as long as it is a technology that can identify the subject. Examples of image recognition include facial recognition.

[0033] The accompanying person selection unit 12 selects from a group of aforementioned persons who are in the same time period as accompanying persons (S12, accompanying person selection procedure).

[0034] The companion selection unit 12 may, for example, perform the process of selecting companions based on the aforementioned time period, based on the period from the entry time to the exit time. Specifically, the companion selection unit 12 may, for example, select companions who are in the same time period from the entry time to the exit time.

[0035] The group formation unit 13 forms groups consisting of the accompanying persons for each specific area (S13, group formation procedure).

[0036] The group formation unit 13 may, for example, perform the group formation process as a process of associating group identification information and specific area identification information with the groups. The group identification information may, for example, be an identification number that can identify the group. The specific area identification information may, for example, be an identification number that can identify the specific area. The group formation unit 13 may, for example, store the group correspondence information, which associates the group identification information and the specific area identification information with the groups, in the form of a database. The group formation unit 13 may, for example, store the group correspondence information in the memory 102 or storage device 104 of the device 10, or in the memory or storage device of another device other than the device 10.

[0037] The attribute information acquisition unit 14 acquires attribute information relating to the attributes of the subject persons who constitute the group (S14, attribute information acquisition procedure).

[0038] The attribute information is, for example, information about the attributes of the subject persons who make up the group. The attribute information may include, for example, information about gender, information about age group, information about the number of people in each age group, and information about combinations thereof. The information about gender may include, for example, male, female, etc. The information about age group may include, for example, infants and younger, children, students, young people, parents, grandparents, etc. The students may include, for example, elementary school students, junior high school students, high school students, university students, etc. The information about the number of people in each age group may include, for example, one person, two or more people, etc. The information about combinations thereof may include, for example, infants and younger, children, male students, female students, young men, young women, fathers, mothers, grandfathers, and grandmothers, etc.

[0039] The attribute information acquisition unit 14 may, for example, acquire a body image including all or part of the subject's body from an imaging device placed in the specific area, extract feature quantities of all or part of the subject's body from the body image, and acquire the attribute information based on image recognition using the feature quantities. The attribute information acquisition unit 14 may, for example, perform the attribute information acquisition process based on the image recognition using known application software related to image recognition. The body image may be, for example, a face image. The image recognition is, for example, facial recognition when the body image is a face image.

[0040] The attribute information acquisition unit 14 may, for example, acquire the attribute information from the memory 102 or storage device 104 of the device 10, or it may acquire it from the memory or storage device of another device other than the device 10.

[0041] The category classification unit 15 classifies the group into a predetermined category based on the attribute information (S15, category classification procedure).

[0042] The classification process by the category classification unit 15 may be performed, for example, based on correspondence information that associates the attribute information with the predetermined category. An example of the correspondence information is shown in Figure 4. In Figure 4, the attribute information is shown as information that combines, for example, information about gender, information about age group, and information about the number of people in the age group. In Figure 4, the attribute information is shown as, for example, infants and younger, children, male students, female students, young men, young women, fathers, mothers, grandfathers, and grandmothers. In Figure 4, the predetermined category is shown as, for example, child-rearing generation of pattern 1 (child-rearing generation 1), child-rearing generation of pattern 2 (child-rearing generation 2), three-generation household of pattern 1 (three-generation household 1), three-generation household of pattern 2 (three-generation household 2), friend of pattern 1 (friend 1), friend of pattern 2 (friend 2), friend of pattern 3 (friend 3), friend of pattern 4 (friend 4), friend of pattern 5 (friend 5), friend of pattern 6 (friend 6), and couples. As shown in Figure 4, the attribute information and the predetermined category are associated with each other, for example, in the correspondence information.

[0043] The category classification unit 15 may, for example, perform classification processing based on the correspondence information shown in Figure 4 as follows. Specifically, the category classification unit 15 may, for example, classify the group as a child-rearing generation of Pattern 1 if the group consists of infants or younger (one or more people), a father, and a mother. The category classification unit 15 may, for example, classify the group as a child-rearing generation of Pattern 2 if the group consists of infants or younger (one or more people), a child (one or more people), a father, and a mother. The category classification unit 15 may, for example, classify the group as a three-generation household of Pattern 1 if the group consists of infants or younger (one or more people), a father, a mother, a grandfather, and a grandmother. The category classification unit 15 may, for example, classify the group as a three-generation household of Pattern 2 if the group consists of infants or younger (one or more people), a child (one or more people), a father, a mother, a grandfather, and a grandmother. The category classification unit 15 classifies the group into the "friends" category of Pattern 1, for example, if the group consists of multiple male students. The category classification unit 15 classifies the group into the "friends" category of Pattern 2, for example, if the group consists of multiple female students. The category classification unit 15 classifies the group into the "friends" category of Pattern 3, for example, if the group consists of multiple male students and multiple female students. The category classification unit 15 classifies the group into the "friends" category of Pattern 4, for example, if the group consists of multiple young men. The category classification unit 15 classifies the group into the "friends" category of Pattern 5, for example, if the group consists of multiple young women. The category classification unit 15 classifies the group into the "friends" category of Pattern 6, for example, if the group consists of multiple young men and multiple young women. The category classification unit 15 classifies the group into the "couples" category, for example, if the group consists of one young man and one young woman.

[0044] The category classification method of this disclosure (hereinafter also referred to as the method of this disclosure) is a method that is implemented by, for example, replacing each "procedure" in the program of this disclosure with a "process". Specifically, the method of this disclosure includes, for example, a time acquisition process, a companion subject extraction process, a group formation process, an attribute information acquisition process, and a category classification process. The time acquisition process acquires the time period when each subject was in a specific area. The companion subject extraction process extracts subjects who are in the same time period from among multiple subjects as companion subjects. The group formation process forms groups composed of the companion subjects for each specific area. The attribute information acquisition process acquires attribute information regarding the attributes of the subjects constituting the group. The category classification process classifies the groups into predetermined categories based on the attribute information. The method of this disclosure can be implemented, for example, using the apparatus 10 of this disclosure shown in Figure 1 or Figure 2. However, the method of this disclosure is not limited to, for example, a method using the apparatus 10 of this disclosure. The methods described herein can be applied, for example, by reference to the descriptions in the Program and Apparatus of the Disclosure.

[0045] As described above, according to the category classification program of this disclosure, the time acquisition procedure acquires the time period when each subject was in a specific area, the accompanying subject extraction procedure extracts subjects who were in the same time period as the aforementioned subjects from among multiple subjects as accompanying subjects, the group formation procedure forms groups composed of the accompanying subjects for each specific area, the attribute information acquisition procedure acquires attribute information regarding the attributes of the subjects constituting the group, and the category classification procedure classifies the group into a predetermined category based on the attribute information. Therefore, according to this disclosure, categories can be classified for appropriately formed groups. Furthermore, according to this disclosure, for example, the relationship between each category and the average customer spending can be grasped, and measures to improve facility usage targeting categories with high average customer spending or measures to improve average customer spending targeting categories with low average customer spending can be implemented. Furthermore, according to this disclosure, for example, behavioral data and purchase data for each category can be grasped and used to plan measures to increase sales.

[0046] [Embodiment 2] Another example of the category classification program described herein is explained.

[0047] Figure 5 is a block diagram showing an example configuration of a category classification device 10A. As shown in Figure 5, the category classification device 10A includes a distance acquisition unit 16 in place of the time acquisition unit 11 in the configuration of the category classification device 10 of Embodiment 1. Note that the category classification device 10A shown in Figure 5 may also include a distance acquisition unit 16 in addition to the configuration of the category classification device 10 of Embodiment 1 (not shown). The hardware configuration of the category classification device 10A is the same as that of the category classification device 10 of Figure 2, except that the central processing unit 101 has the configuration of the category classification device 10A of Figure 5 in place of the configuration of the category classification device 10 of Figure 1. Note that, for example, the descriptions of other embodiments can be referenced in this disclosure.

[0048] Another example of processing by the category classification program of this disclosure will be described in more detail with reference to Figure 6. Figure 6 is a flowchart of an example of each step of the category classification program of this disclosure. The category classification program of this disclosure can be implemented, for example, using the apparatus 10A of this disclosure shown in Figure 5. However, the category classification program of this disclosure is not limited to a program that uses the apparatus 10A of this disclosure. The processing of the distance acquisition unit 16 will be described below. The processing of the distance acquisition unit 16 can be inserted at any appropriate position in the flowchart of Figure 3 described in Embodiment 1, for example, but as shown in Figure 6, the processing of the distance acquisition unit 16 may be inserted, for example, in place of the processing of the time acquisition unit 11. The processing of the distance acquisition unit 16 may be executed in parallel with the processing of the time acquisition unit 11, for example (not shown).

[0049] The distance acquisition unit 16 acquires, for example, the distance between the subjects in the specific area (S16, distance acquisition procedure). S16 may be performed, for example, in place of or in addition to S11 in Embodiment 1.

[0050] The distance acquisition unit 16 may acquire the distance between the subjects based on position estimation, for example.

[0051] The distance acquisition unit 16 may, for example, perform the process of acquiring the distance between the subjects based on the distance between the coordinates of the subjects. Specifically, the distance acquisition unit 16 may, for example, acquire the coordinates of each subject estimated by the position estimation, and acquire the distance between the coordinates of the subjects as the distance between the subjects. The coordinates may be, for example, coordinates in real space or coordinates in virtual space. The position estimation may be any technology capable of estimating the position of the subjects, and the form may be any. Examples of the position estimation include position estimation using radio wave sensors and position estimation using optical sensors.

[0052] The position estimation using the radio wave sensor is a technique for estimating the position of a subject based on the transmission and reception of radio waves between the radio wave sensor and the radio wave transmitter. The number of radio wave sensors to be arranged may be, for example, any number that allows the position of the subject to be estimated. For example, if position estimation is performed by three-point positioning, the number of radio wave sensors may be three. Examples of radio wave sensors include Wi-Fi® packet sensors and beacon receivers. The radio wave sensor may be, for example, a device owned by the subject or a device placed in the specific area. The radio wave transmitter may be, for example, a device owned by the subject or a device placed in the specific area. If the radio wave sensor is a Wi-Fi® packet sensor placed in the specific area, the radio wave transmitter may be, for example, a device owned by the subject (e.g., a smartphone). If the radio wave sensor is a beacon receiver owned by the subject (e.g., a smartphone), the radio wave transmitter may be, for example, a device placed in the specific area (e.g., a beacon transmitter).

[0053] The position estimation using the aforementioned optical sensor is a technique for estimating the position of a target by, for example, irradiating the target with light from an optical illumination device and detecting the reflected light from the target with an optical sensor. Examples of the position estimation using the optical sensor include 2D LiDAR, 3D LiDAR, etc. Examples of the optical illumination device include radar illumination devices, etc. Examples of the optical sensor include radar detection devices, etc. The optical illumination device and the optical sensor may be, for example, devices arranged in the specific area.

[0054] The companion selection unit 12, for example, selects companions from a plurality of companions who are close in distance for a predetermined period of time or longer (S12A, companion selection procedure). S12A may be performed, for example, in place of or in addition to S12 in Embodiment 1.

[0055] The companion subject extraction unit 12 may, for example, perform the companion subject extraction process based on the determination result of whether the distance between the subjects is close or not. Specifically, the companion subject extraction unit 12 may, for example, determine whether the distance between the subjects is less than or equal to a distance threshold, or whether the distance between the subjects is less than a distance threshold. If the companion subject extraction unit 12 determines, for example, that the distance between the subjects is less than or equal to the distance threshold, or if the distance between the subjects is less than the distance threshold, it determines that the distance between the subjects is close. However, if the companion subject extraction unit 12 determines, for example, that the distance between the subjects exceeds the distance threshold, or if the distance between the subjects is greater than or equal to the distance threshold, it may determine that the distance between the subjects is not close. The companion selection unit 12, for example, if it determines that the distance between the subjects is close, determines whether the close proximity state between the subjects has been maintained for a predetermined period of time or longer. The companion selection unit 12 extracts the subjects who have been determined to be close in distance from each other and whose proximity state has been maintained for a predetermined period of time or longer as companion subjects. The distance threshold and the predetermined period may be set appropriately depending on the type of the specific area, for example. The distance threshold may be 5m to 10m if the specific area is the entrance area or the exit area. The predetermined period may be 90 seconds if the specific area is the entrance area or the exit area.

[0056] The predetermined period may be, for example, a correction period. The correction period is, for example, the period during which, if the specific area is the entrance area or the exit area, a correction corresponding to the width of the entrance in the entrance area or the width of the exit in the exit area is made to the predetermined period. The group enters and exits the specific area in a formation corresponding to the width of the entrance and the width of the exit. Specifically, if the width of the entrance and the width of the exit are narrow, the group enters and exits the specific area in a formation arranged in a single line horizontally. For this reason, the correction to the predetermined period is, for example, an extension of the predetermined period if the width of the entrance and the width of the exit are narrow. On the other hand, if the width of the entrance and the width of the exit are wide, the group enters and exits the specific area in a formation arranged in a single line vertically. For this reason, the correction to the predetermined period is, for example, a shortening of the predetermined period if the width of the entrance and the width of the exit are wide. The range of extension and shortening of the predetermined period may be set appropriately, for example, according to the width of the inlet and the width of the outlet.

[0057] As described above, S16 and S12A may be executed in parallel with S11 and S12, for example, if the device 10A includes a distance acquisition unit 16 in addition to the time acquisition unit 11. S11 and S12 may be executed in the same manner as S11 and S12 in Embodiment 1, for example.

[0058] Steps S13 to S15 are performed, for example, in the same manner as steps S13 to S15 in Embodiment 1.

[0059] Furthermore, if the device 10A includes a distance acquisition unit 16 in addition to the time acquisition unit 11, the group formation unit 13 may form a group consisting of individuals who are included in both the accompanying persons extracted by S12 and the accompanying persons extracted by S12A.

[0060] The categorization method of this disclosure (hereinafter also referred to as the method of this disclosure) is a method implemented by, for example, replacing each "procedure" in the program of this disclosure with a "process". Specifically, the method of this disclosure further includes, for example, a distance acquisition process, the distance acquisition process which acquires the distance between the subjects in the specific area, and the accompanying subject extraction process which extracts subjects who are close in distance from the subjects as accompanying subjects from among the subjects. The method of this disclosure can be implemented, for example, using the apparatus 10A of this disclosure shown in Figure 5. However, the method of this disclosure is not limited to, for example, a method using the apparatus 10A of this disclosure. The method of this disclosure can be implemented by referring to, for example, the descriptions in the program and the apparatus of this disclosure.

[0061] As described above, according to the category classification program of this disclosure, for example, the distance between subjects in the specified area can be obtained by the distance acquisition procedure, and subjects who are close in distance from the subjects can be extracted from a group of subjects as accompanying subjects by the accompanying subject extraction procedure. Therefore, according to this disclosure, for example, appropriate groups can be formed based on the distance between subjects. Furthermore, according to this disclosure, for example, categories can be classified for such groups.

[0062] [Embodiment 3] Another example of the category classification program described herein is explained.

[0063] Figure 7 is a block diagram showing an example configuration of the category classification device 10B. As shown in Figure 7, the category classification device 10B includes a provisional group formation unit 17 and a duplicate target extraction unit 18 in addition to the configuration of the category classification device 10 of Embodiment 1. The hardware configuration of the category classification device 10B is the same as that of the category classification device 10 in Figure 2, except that the central processing unit 101 has the configuration of the category classification device 10B in Figure 7 instead of the configuration of the category classification device 10 in Figure 1. The embodiments of this disclosure can be described by referring to, for example, the descriptions of other embodiments.

[0064] Another example of processing by the category classification program of this disclosure will be described in more detail with reference to Figure 8. Figure 8 is a flowchart of an example of each step of the category classification program of this disclosure. The category classification program of this disclosure can be implemented, for example, using the apparatus 10B of this disclosure shown in Figure 7. However, the category classification program of this disclosure is not limited to a program using the apparatus 10B of this disclosure. The processing of the provisional group formation unit 17 and the duplicate target extraction unit 18 will be described below. The processing of the provisional group formation unit 17 and the duplicate target extraction unit 18 can be appropriately inserted at any position in the flowchart of Figure 3 described in Embodiment 1, for example, but as shown in Figure 8, it is preferable that the processing of the provisional group formation unit 17 and the duplicate target extraction unit 18 be inserted, for example, after S12.

[0065] Steps S11 to S12 are performed, for example, in the same manner as steps S11 to S12 in Embodiment 1.

[0066] The provisional group formation unit 17, for example, if the specific area is an entrance area related to the entrance to the facility, forms a group consisting of the accompanying persons as a provisional group upon entry to the facility, and if the specific area is an exit area related to the exit from the facility, forms a group consisting of the accompanying persons as a provisional group upon exit from the facility (S17, provisional group formation procedure).

[0067] The provisional group formation unit 17 may, for example, perform the formation process of the provisional group upon entry to the facility and the provisional group upon exit from the facility as a process of associating provisional group identification information and specific area identification information with the provisional group upon entry to the facility and the provisional group upon exit from the facility. The provisional group identification information may, for example, be an identification number that can identify the provisional group upon entry to the facility and the provisional group upon exit from the facility. The specific area identification information may, for example, be an identification number that can identify the entrance area related to the entrance to the facility and the exit area related to the exit from the facility. The provisional group formation unit 17 may, for example, store the group correspondence information, which associates the provisional group identification information and the specific area identification information with the provisional group upon entry to the facility and the provisional group upon exit from the facility, in database format. The provisional group formation unit 17 may, for example, store the group correspondence information in the memory 102 or storage device 104 of this device 10, or in the memory or storage device of another device other than this device 10.

[0068] The duplicate target extraction unit 18 extracts, for example, duplicate target individuals who are included in both the provisional group for entering the facility and the provisional group for leaving the facility from the provisional group for entering the facility and the provisional group for leaving the facility (S18, duplicate target extraction procedure).

[0069] The group formation unit 13 forms a group consisting of the overlapping individuals as the group (S13A, group formation procedure). The group formation process by the group formation unit 13 may be described by referring to the group formation process by the group formation unit 13 in Embodiment 1, for example.

[0070] Steps S14 to S15 are performed, for example, in the same manner as steps S14 to S15 in Embodiment 1.

[0071] The category classification method of this disclosure (hereinafter also referred to as the method of this disclosure) is a method that is implemented by, for example, replacing each "procedure" in the program of this disclosure with "process". Specifically, the method of this disclosure further includes, for example, a provisional group formation process and a duplicate subject extraction process, wherein the provisional group formation process forms a group consisting of the accompanying subjects as a provisional group upon entry to the facility if the specific area is an entrance area relating to the entrance to the facility, and forms a group consisting of the accompanying subjects as a provisional group upon exiting the facility if the specific area is an exit area relating to the exit from the facility, the duplicate subject extraction process extracts duplicate subjects who are included in both the provisional group upon entry to the facility and the provisional group upon exiting the facility, and the group formation process forms a group consisting of the duplicate subjects as the group. The method of this disclosure can be implemented, for example, using the apparatus 10B of this disclosure shown in Figure 7. The methods disclosed herein are not limited to, for example, methods using the apparatus 10B of the Disclosure. The methods disclosed herein may, for example, be based on the descriptions in the program and the apparatus of the Disclosure.

[0072] As described above, according to the category classification program of this disclosure, for example, by the provisional group formation procedure, if the specific area is an entrance area related to the entrance to the facility, a group consisting of the accompanying persons can be formed as a provisional group at the time of facility entry, and if the specific area is an exit area related to the exit from the facility, a group consisting of the accompanying persons can be formed as a provisional group at the time of facility exit, and by the duplicate subject extraction procedure, duplicate subjects who are included in both the provisional group at the time of facility entry and the provisional group at the time of facility exit can be extracted from the provisional group at the time of facility entry and the provisional group at the time of facility exit, and by the group formation procedure, a group consisting of the duplicate subjects can be formed as the group. For this reason, according to this disclosure, for example, by forming groups at the entrance to the facility and the exit from the facility, which are areas where the probability of group formation is high, more appropriate groups can be formed. Furthermore, according to this disclosure, for example, categories can be classified for such groups. Furthermore, according to this disclosure, for example, the usage status of specific areas within the facility can be analyzed retrospectively for groups formed after the subjects have left the facility.

[0073] [Embodiment 4] Another example of the category classification program described herein is explained.

[0074] Figure 9 is a block diagram showing the configuration of an example of a category classification device 10C. As shown in Figure 9, the category classification device 10C includes a score assignment unit 19, a suitability determination unit 20, and a setting unit 21 in addition to the configuration of the category classification device 10 of Embodiment 1. The hardware configuration of the category classification device 10C is the same as that of the category classification device 10 in Figure 2, except that the central processing unit 101 has the configuration of the category classification device 10C in Figure 9 instead of the configuration of the category classification device 10 in Figure 1. Furthermore, embodiments of this disclosure can be described by referring to, for example, the descriptions of other embodiments.

[0075] Another example of processing by the category classification program of this disclosure will be described in more detail with reference to Figure 10. Figure 10 is a flowchart of an example of each step of the category classification program of this disclosure. The category classification program of this disclosure can be implemented, for example, using the apparatus 10C of this disclosure shown in Figure 9. However, the category classification program of this disclosure is not limited to a program that uses the apparatus 10C of this disclosure. The processing of the scoring unit 19, the suitability determination unit 20, and the setting unit 21 will be described below. The processing of the scoring unit 19, the suitability determination unit 20, and the setting unit 21 can be appropriately inserted at any position in the flowchart of Figure 3 described in Embodiment 1, for example, but as shown in Figure 10, it is preferable that the processing of the scoring unit 19, the suitability determination unit 20, and the setting unit 21 be inserted, for example, after S13.

[0076] Steps S11 to S13 are performed, for example, in the same manner as steps S11 to S13 in Embodiment 1.

[0077] The score-assigning unit 19, for example, assigns a score to the group corresponding to the type of the specific area when the group is formed by the group-forming unit 13 (S19, score-assigning procedure).

[0078] The score assignment unit 19 may, for example, perform the score assignment process based on score correspondence information that associates scores with the types of specific areas. The score correspondence information may, for example, be information that associates a higher score with the specific area that has a high probability of being in the group. Examples of specific areas that have a high probability of being in the group include the entrance area, the exit area, the photo spot area, the food and beverage area, the attraction area, etc. The score correspondence information may, for example, have the following correspondence relationships. However, the score correspondence information is not limited to the following correspondence relationships. For example, if the specific area is the entrance area or the exit area, the score correspondence information may associate it with a score of 50 points. For example, if the specific area is the photo spot area, the score correspondence information may associate it with a score of 30 points. For example, if the specific area is the food and beverage area, the score correspondence information may associate it with a score of 15 points. For example, if the specific area is the attraction area, the score correspondence information may associate it with a score of 10 points. The score correspondence information may, for example, appropriately set scores to correspond to the type of the specific area according to the type of facility. The score assignment unit 19 may, for example, associate the assigned scores with the group correspondence information as score information.

[0079] The suitability determination unit 20 determines, for example, whether the score assigned to the group conforms to a predetermined standard (S20, suitability determination procedure).

[0080] The suitability determination unit 20 may, for example, perform the determination process of whether the score conforms to the predetermined criteria as a determination process of whether the score is equal to or greater than a score threshold, or a determination process of whether the score exceeds a score threshold. Specifically, the suitability determination unit 20 may, for example, determine whether the score is equal to or greater than a score threshold, or whether the score exceeds a score threshold. If the suitability determination unit 20 determines, for example, that the score conforms to the predetermined criteria, or if it determines that the score is equal to or greater than a score threshold, or if it determines that the score exceeds a score threshold, the suitability determination unit 20 may determine that the score does not conform to the predetermined criteria. The score threshold may be set appropriately, for example, according to the number of specific areas in the facility. The score threshold may be, for example, 100 points.

[0081] For example, if the suitability determination unit 20 determines that the score assigned to the group conforms to the predetermined criteria, the setting unit 21 sets the group as a suitable group (S21, setting procedure).

[0082] The setting unit 21 may, for example, perform the setting process for the conforming group as a process of associating conforming group identification information with the group. The conforming group identification information may, for example, be an identification number that can identify the conforming group. The setting unit 21 may, for example, associate the conforming group identification information with the group correspondence information. The setting unit 21 may, for example, store the group correspondence information, to which the conforming group identification information is associated, in database format. The setting unit 21 may, for example, store the group correspondence information in the memory 102 or storage device 104 of the device 10, or in the memory or storage device of another device other than the device 10.

[0083] The attribute information acquisition unit 14 acquires, for example, attribute information relating to the attributes of the subject persons constituting the conforming group (S14A, attribute information acquisition procedure). The attribute information acquisition process by the attribute information acquisition unit 14 may be carried out by referring to, for example, the description of the attribute information acquisition process by the attribute information acquisition unit 14 in Embodiment 1.

[0084] The category classification unit 15 classifies the conforming group into a predetermined category based on the attribute information, for example (S15A, category classification procedure). The classification process to a predetermined category by the category classification unit 15 may be carried out by referring to, for example, the description of the classification process to a predetermined category by the category classification unit 15 in Embodiment 1.

[0085] The category classification method of this disclosure (hereinafter also referred to as the method of this disclosure) is a method that is carried out by, for example, replacing each "procedure" in the program of this disclosure with "process". Specifically, the method of this disclosure further includes, for example, a scoring process, a suitability determination process, and a setting process, wherein the scoring process assigns a score corresponding to the type of specific area to the group if the group is formed by the group formation process, the suitability determination process determines whether the score assigned to the group conforms to predetermined criteria, the setting process sets the group as a suitable group if the suitability determination process determines that the score assigned to the group conforms to the predetermined criteria, the attribute information acquisition process acquires attribute information relating to the attributes of the subjects constituting the suitable group, and the category classification process classifies the suitable group into predetermined categories based on the attribute information. The method of this disclosure can be carried out, for example, using the apparatus 10C of this disclosure shown in Figure 9. However, the method of this disclosure is not limited to, for example, a method using the apparatus 10C of this disclosure. The methods described herein can be applied, for example, by reference to the descriptions in the Program and Apparatus of the Disclosure.

[0086] As described above, according to the category classification program of this disclosure, for example, a scoring procedure assigns a score to the group corresponding to the type of specific area when the group is formed according to the group formation procedure, a suitability determination procedure determines whether the score assigned to the group conforms to predetermined criteria, a setting procedure sets the group as a suitable group if the suitability determination procedure determines that the score assigned to the group conforms to the predetermined criteria, an attribute information acquisition procedure acquires attribute information regarding the attributes of the subjects constituting the suitable group, and a category classification procedure classifies the suitable group into predetermined categories based on the attribute information. Therefore, according to this disclosure, for example, an appropriate group can be formed while the subjects are staying in the facility. Furthermore, according to this disclosure, for example, a category can be classified for such a group.

[0087] [Embodiment 5] Another example of the category classification program described herein is explained.

[0088] Figure 11 is a block diagram showing the configuration of an example of a category classification device 10D. As shown in Figure 11, the category classification device 10D includes a service content adjustment unit 22 in addition to the configuration of the category classification device 10C of Embodiment 4. The hardware configuration of the category classification device 10D is the same as that of the category classification device 10 in Figure 2, except that the central processing unit 101 has the configuration of the category classification device 10D in Figure 1 instead of the configuration of the category classification device 10 in Figure 1. The embodiments of this disclosure can be described by referring to, for example, the descriptions of other embodiments.

[0089] Another example of processing by the category classification program of this disclosure will be described in more detail with reference to Figure 12. Figure 12 is a flowchart of an example of each step of the category classification program of this disclosure. The category classification program of this disclosure can be implemented, for example, using the apparatus 10D of this disclosure shown in Figure 11. However, the category classification program of this disclosure is not limited to a program that uses the apparatus 10D of this disclosure. The processing of the service content adjustment unit 22 will be described below. The processing of the service content adjustment unit 22 can be inserted at any appropriate position in the flowchart of Figure 10 described in Embodiment 4, for example, but as shown in Figure 12, it is preferable that the processing of the service content adjustment unit 22 be inserted, for example, after S22.

[0090] Steps S11 to S13 are performed, for example, in the same manner as steps S11 to S13 in Embodiment 1.

[0091] Steps S19 to S21 and S14A to S15A are performed, for example, in the same manner as steps S19 to S21 and S14A to S15A in Embodiment 4.

[0092] The service content adjustment unit 22 adjusts the service content to be provided to the conforming group based on the predetermined category to which the conforming group belongs (S22, service content adjustment procedure).

[0093] The service content adjustment unit 22 may, for example, perform at least one of the following as the service content adjustment process: adjustment of table arrangement, adjustment of offerings, adjustment of staff arrangement, adjustment of recommendation information, and adjustment of announcement information.

[0094] The adjustment of the table arrangement may, for example, be adjusted in the order of the tables in the specific area according to the number of people in the predetermined category to which the suitable group belongs. For example, if the number of people in the predetermined category to which the suitable group belongs is two (e.g., friends, couples, etc.), the table arrangement may be adjusted so that there are more tables for two. For example, if the predetermined category to which the suitable group belongs is a family with children or a multi-generational household, the table arrangement may be adjusted so that there are more tables for groups.

[0095] The adjustment of the offerings may be carried out, for example, as an adjustment to the offerings corresponding to the predetermined category to which the conforming group belongs. Examples of such adjustments to the offerings include adjustments to the types of dishes, and adjustments to the preparation associated with the adjustments to the types of dishes.

[0096] The adjustment of staff allocation may be made, for example, if the designated category to which the suitable group belongs includes at least one of infants or younger children (e.g., families with young children, multi-generational households, etc.), so that there are more staff to assist in assisting with infants and younger children. Examples of assistance with infants and younger children include, if the designated area is related to the attraction, ensuring that seat belts are worn when riding the attraction. Examples of assistance with infants and younger children include, if the designated area is related to food and beverages, placing high chairs for children in the back area in advance.

[0097] The adjustment of the recommendation information may be, for example, by changing the display position of the recommendation information so that, if the predetermined category to which the matching group belongs is a three-generation household, the recommendation information can be easily understood by the grandparents. The recommendation information may include, for example, menus for infants and children if the specific area is an area related to food and beverages. The display targets for the recommendation information may include, for example, the display section of a digital signage or the display section of a ticket vending machine.

[0098] The adjustment of the announcement information may be carried out, for example, as an adjustment to the announcement content corresponding to the predetermined category to which the conforming group belongs. Examples of announcements included in the announcement information include announcements regarding guidance, announcements regarding time sales, announcements regarding events, and so on.

[0099] The category classification method of this disclosure (hereinafter also referred to as the method of this disclosure) is a method implemented by, for example, replacing each "procedure" in the program of this disclosure with a "process". Specifically, the method of this disclosure further includes, for example, a service content adjustment process, the service content adjustment process adjusting the service content provided to the conforming group based on the predetermined category to which the conforming group belongs. The method of this disclosure can be implemented, for example, using the apparatus 10D of this disclosure shown in Figure 11. However, the method of this disclosure is not limited to, for example, a method using the apparatus 10D of this disclosure. The method of this disclosure can be implemented by, for example, drawing on the descriptions in the program and the apparatus of this disclosure.

[0100] As described above, according to the category classification program of this disclosure, for example, the service content provided to the conforming group can be adjusted based on the predetermined category to which the conforming group belongs, through a service content adjustment procedure. Therefore, according to this disclosure, for example, the content of the services provided to the subject while the subject is staying in the facility can be appropriately adjusted according to the category of the group staying in the facility. Furthermore, according to this disclosure, for example, a subject staying in the facility can enjoy services corresponding to the category of the group to which the subject belongs.

[0101] [Embodiment 6] The following describes an example of how the device described in this disclosure may be used. However, this disclosure is not limited to the following description.

[0102] First, the device of this disclosure forms a suitable group from subjects using an amusement park during their stay, and categorizes the suitable group. The device of this disclosure is capable of communicating with imaging devices placed in specific areas of the amusement park via a wireless communication network. Subjects A and B, for example, pass through the entrance area of ​​the amusement park at the same time. Subjects A and B are a young man and woman. In this case, the imaging device placed in the entrance area acquires the start time when image recognition begins when subjects A and B enter the entrance area, and the end time when image recognition ends when subjects A and B leave the entrance area. Since the period from the start time to the end time in the entrance area is the same for subjects A and B, the device of this disclosure stores the group consisting of subjects A and B in its storage device. The device of this disclosure stores a score of 50 points corresponding to the entrance area, associating it with the group. Furthermore, subjects A and B stay in an area related to a photo spot, for example, at the same time. In this case, the imaging device placed in the area related to the photo spot acquires the start time when image recognition begins when subjects A and B enter the area related to the photo spot, and the end time when image recognition ends when subjects A and B leave the area related to the photo spot. The device of this disclosure stores the group consisting of subjects A and B in its storage device because the period from the start time to the end time in the area related to the photo spot is the same time for subjects A and B. The device of this disclosure stores a score of 30 points, which is the score corresponding to the area related to the photo spot, in association with the group. The device of this disclosure determines that the score conforms to a predetermined standard because the score assigned to the group consisting of subjects A and B is 80 points or more, which is the score threshold, and sets subjects A and B as a conforming group. The device of this disclosure acquires the gender, age group, and number of subjects A and B as attribute information of subjects A and B that constitute the conforming group. The apparatus of this disclosure classifies the matching group into a couple category based on the attribute information.Thus, according to this disclosure, for example, it is possible to form appropriate groups while the subjects are staying in the facility, and to classify the formed groups into categories.

[0103] Next, the device of this disclosure, for example, forms a group after the subjects return home from the amusement park and categorizes the group. Subjects A and B return home, for example, by entering the entrance area of ​​the amusement park at the same time and exiting the exit area at the same time. An imaging device located in the entrance area acquires the start time when image recognition begins when subjects A and B enter the entrance area and the end time when image recognition ends when subjects A and B exit the entrance area. Since the period from the start time to the end time in the entrance area is the same time period for subjects A and B, the device of this disclosure stores the group consisting of subjects A and B in its storage device as a provisional group at the time of facility entry. An imaging device located in the exit area acquires the start time when image recognition begins when subjects A and B enter the exit area and the end time when image recognition ends when subjects A and B exit the exit area. The device of this disclosure stores a group consisting of subjects A and B in its storage device as a provisional group at the time of facility exit, since the period from the start time to the end time in the exit area is the same for subjects A and B. The device of this disclosure extracts subjects A and B who are included in both the provisional group at the time of facility entry and the provisional group at the time of facility exit, forms a group consisting of subjects A and B, and stores it in its storage device. The device of this disclosure obtains attribute information of subjects A and B that constitute the group, including their gender, age group, and number of people. Based on the attribute information, the device of this disclosure classifies the suitable group into the category of a couple. In this way, according to this disclosure, it is possible to classify categories for appropriately formed groups. Furthermore, according to this disclosure, for example, it is possible to retrospectively analyze the usage status of a specific area within the facility for groups formed after subjects have left the facility.

[0104] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be made as understandable to those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0105] <Note> Some or all of the above embodiments may be described as follows, but are not limited to the following: (Note 1) This includes procedures for obtaining timing, extracting accompanying persons, forming groups, obtaining attribute information, and categorizing. The aforementioned procedure for obtaining the time period involves obtaining the time period during which each subject was in a specific area, The procedure for selecting accompanying persons involves selecting from multiple persons that are in the same time period as accompanying persons, The group formation procedure involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons who constitute the group, The aforementioned category classification procedure classifies the group into a predetermined category based on the attribute information. A category classification program that causes a computer to perform each of the above steps. (Note 2) In lieu of or in addition to the aforementioned time acquisition procedure, a distance acquisition procedure is further included: The distance acquisition procedure acquires the distance between the subjects in the specified area, The procedure for selecting accompanying persons involves selecting persons who are close in distance for a predetermined period of time or longer from among a group of persons as accompanying persons. The category classification program described in Appendix 1. (Note 3) The distance acquisition procedure acquires the distance between the subjects based on position estimation. The category classification program described in Appendix 2. (Note 4) The aforementioned specific area is an area included in the facility. The aforementioned specific area includes at least one of the entrance area and the exit area. The aforementioned entrance area includes an entrance area relating to the entrance to the facility and an entrance area relating to the entrance to a passage within the facility. The aforementioned exit area includes an exit area relating to an exit from the facility, and an exit area relating to an exit from a passage within the facility. A category classification program as described in any one of the appendices 1 to 3. (Note 5) This further includes a procedure for forming a provisional group and a procedure for identifying duplicate individuals. The aforementioned provisional group formation procedure is: If the aforementioned specific area is an entrance area related to the entrance to the facility, the group consisting of the accompanying persons shall be formed as a provisional group upon entry to the facility, and If the aforementioned specific area is an exit area related to the exit from the facility, the group consisting of the accompanying persons shall be formed as a provisional group at the time of leaving the facility. The procedure for extracting duplicate individuals involves extracting duplicate individuals who are included in both the provisional group for entering the facility and the provisional group for leaving the facility from the provisional group for entering the facility and the provisional group for leaving the facility. The group formation procedure involves forming a group consisting of the overlapping individuals as the group. The category classification program described in Appendix 4. (Note 6) This further includes a scoring procedure, a suitability determination procedure, and a setting procedure. The scoring procedure, when the group is formed by the group formation procedure, assigns a score to the group corresponding to the type of the specific area. The aforementioned suitability determination procedure determines whether the score assigned to the group conforms to a predetermined standard, The setting procedure, if the score assigned to the group is determined by the suitability determination procedure to conform to the predetermined criteria, sets the group as a conforming group. The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons constituting the conforming group, The aforementioned category classification procedure classifies the conforming group into a predetermined category based on the attribute information. A category classification program as described in any one of the items 1 through 5 of the appendix. (Note 7) This further includes the procedure for adjusting service details, The service content adjustment procedure adjusts the service content provided to the conforming group based on the predetermined category to which the conforming group belongs. The category classification program described in Appendix 6. (Note 8) It includes a timing acquisition unit, a companion target extraction unit, a group formation unit, an attribute information acquisition unit, and a category classification unit, The aforementioned time acquisition unit acquires the time period during which each subject was in a specific area, The aforementioned accompanying person extraction unit extracts from a group of aforementioned persons the persons who are in the same time period as accompanying persons, The group formation unit forms groups composed of the accompanying persons for each specific area, The attribute information acquisition unit acquires attribute information relating to the attributes of the subject persons constituting the group, The category classification unit classifies the group into a predetermined category based on the attribute information. Category classification device. (Note 9) In place of or in addition to the aforementioned time acquisition unit, a distance acquisition unit is further included. The distance acquisition unit acquires the distance between the subject persons in the specified area. The aforementioned companion selection unit selects from a group of companions those who are close in distance for a predetermined period of time or longer, as companions. The category classification device described in Appendix 8. (Note 10) The distance acquisition unit acquires the distance between the subjects based on the position estimation. The category classification device described in Appendix 9. (Note 11) The aforementioned specific area is an area included in the facility. The aforementioned specific area includes at least one of the entrance area and the exit area. The aforementioned entrance area includes an entrance area relating to the entrance to the facility and an entrance area relating to the entrance to a passage within the facility. The aforementioned exit area includes an exit area relating to an exit from the facility, and an exit area relating to an exit from a passage within the facility. A category classification device as described in any one of the appendices 8 to 10. (Note 12) It further includes a provisional group formation unit and a duplicate target extraction unit, The aforementioned provisional group formation unit is, If the aforementioned specific area is an entrance area related to the entrance to the facility, the group consisting of the accompanying persons shall be formed as a provisional group upon entry to the facility, and If the aforementioned specific area is an exit area related to the exit from the facility, the group consisting of the accompanying persons shall be formed as a provisional group at the time of leaving the facility. The duplicate target extraction unit extracts duplicate target individuals who are included in both the provisional group for facility entry and the provisional group for facility exit from the provisional group for facility entry and the provisional group for facility exit. The group formation unit forms a group consisting of the overlapping target persons as the group. The category classification device described in Appendix 11. (Note 13) It further includes a scoring unit, a suitability determination unit, and a setting unit, The scoring unit, when the group is formed by the group formation unit, assigns a score to the group corresponding to the type of the specific area. The conformity determination unit determines whether the score assigned to the group conforms to a predetermined standard. The setting unit sets the group as a compliant group if the conformity determination unit determines that the score assigned to the group conforms to the predetermined criteria. The attribute information acquisition unit acquires attribute information relating to the attributes of the subject persons constituting the conforming group. The category classification unit classifies the matching group into a predetermined category based on the attribute information. A category classification device as described in any one of the appendices 8 to 12. (Note 14) It further includes a service content adjustment department, The service content adjustment unit adjusts the service content to be provided to the conforming group based on the predetermined category to which the conforming group belongs. The category classification device described in Appendix 13. (Note 15) This includes a timing acquisition process, a process for selecting accompanying persons, a group formation process, an attribute information acquisition process, and a category classification process. The aforementioned time acquisition process acquires the time period during which each subject was in a specific area, The aforementioned process of selecting accompanying persons involves selecting from a group of persons that are in the same time period as accompanying persons, The group formation step involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition step involves acquiring attribute information relating to the attributes of the subject persons constituting the group, The category classification step involves classifying the group into a predetermined category based on the attribute information. A categorization method in which each of the above steps is performed by a computer. (Note 16) In lieu of or in addition to the aforementioned time acquisition step, a distance acquisition step is further included. The distance acquisition step involves acquiring the distance between the subjects in the specified area. The aforementioned process of selecting accompanying persons involves selecting persons who are close in distance for a predetermined period of time or longer from among a group of persons as accompanying persons. The category classification method described in Appendix 15. (Note 17) The distance acquisition step acquires the distance between the subjects based on the position estimation. The category classification method described in Appendix 16. (Note 18) The aforementioned specific area is an area included in the facility. The aforementioned specific area includes at least one of the entrance area and the exit area. The aforementioned entrance area includes an entrance area relating to the entrance to the facility and an entrance area relating to the entrance to a passage within the facility. The aforementioned exit area includes an exit area relating to an exit from the facility, and an exit area relating to an exit from a passage within the facility. The category classification method described in any one of the items 15 to 17 of the appendix. (Note 19) The process further includes a provisional group formation step and a duplicate target identification step, The aforementioned provisional group formation process is as follows: If the aforementioned specific area is an entrance area related to the entrance to the facility, the group consisting of the accompanying persons shall be formed as a provisional group upon entry to the facility, and If the aforementioned specific area is an exit area related to the exit from the facility, the group consisting of the accompanying persons shall be formed as a provisional group at the time of leaving the facility. The duplicate target extraction step extracts duplicate target individuals who are included in both the provisional group for facility entry and the provisional group for facility exit from the provisional group for facility entry and the provisional group for facility exit. The group formation step involves forming a group consisting of the overlapping target individuals as the group. The category classification method described in Appendix 18. (Note 20) The process further includes a scoring process, a suitability determination process, and a setting process. The scoring step, when the group is formed by the group formation step, assigns a score to the group corresponding to the type of the specific area. The suitability determination step determines whether the score assigned to the group conforms to a predetermined standard. The setting step, if the suitability determination step determines that the score assigned to the group conforms to the predetermined criteria, sets the group as a suitable group. The attribute information acquisition step involves acquiring attribute information relating to the attributes of the subject persons constituting the conforming group. The category classification step classifies the conforming group into a predetermined category based on the attribute information. The category classification method described in any one of the items 15 to 19 of the appendix. (Note 21) This further includes a process for adjusting the service content, The service content adjustment process involves adjusting the service content provided to the conforming group based on the predetermined category to which the conforming group belongs. The category classification method described in Appendix 20. (Note 22) This includes procedures for obtaining timing, extracting accompanying persons, forming groups, obtaining attribute information, and categorizing. The aforementioned procedure for obtaining the time period involves obtaining the time period during which each subject was in a specific area, The procedure for selecting accompanying persons involves selecting from multiple persons that are in the same time period as accompanying persons, The group formation procedure involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons who constitute the group, The aforementioned category classification procedure classifies the group into a predetermined category based on the attribute information. A computer-readable recording medium containing a program that causes a computer to perform each of the aforementioned steps. (Note 23) In lieu of or in addition to the aforementioned time acquisition procedure, a distance acquisition procedure is further included: The distance acquisition procedure acquires the distance between the subjects in the specified area, The procedure for selecting accompanying persons involves selecting persons who are close in distance for a predetermined period of time or longer from among a group of persons as accompanying persons. Recording medium as described in Appendix 22. (Note 24) The distance acquisition procedure acquires the distance between the subjects based on position estimation. Recording medium as described in Appendix 23. (Note 25) The aforementioned specific area is an area included in the facility. The aforementioned specific area includes at least one of the entrance area and the exit area. The aforementioned entrance area includes an entrance area relating to the entrance to the facility and an entrance area relating to the entrance to a passage within the facility. The aforementioned exit area includes an exit area relating to an exit from the facility, and an exit area relating to an exit from a passage within the facility. A recording medium as described in any one of the items 22 to 24 of the appendix. (Note 26) This further includes a procedure for forming a provisional group and a procedure for identifying duplicate individuals. The aforementioned provisional group formation procedure is: If the aforementioned specific area is an entrance area related to the entrance to the facility, the group consisting of the accompanying persons shall be formed as a provisional group upon entry to the facility, and If the aforementioned specific area is an exit area related to the exit from the facility, the group consisting of the accompanying persons shall be formed as a provisional group at the time of leaving the facility. The procedure for extracting duplicate individuals involves extracting duplicate individuals who are included in both the provisional group for entering the facility and the provisional group for leaving the facility from the provisional group for entering the facility and the provisional group for leaving the facility. The group formation procedure involves forming a group consisting of the overlapping individuals as the group. Recording medium as described in Appendix 25. (Note 27) This further includes a scoring procedure, a suitability determination procedure, and a setting procedure. The scoring procedure, when the group is formed by the group formation procedure, assigns a score to the group corresponding to the type of the specific area. The aforementioned suitability determination procedure determines whether the score assigned to the group conforms to a predetermined standard, The setting procedure, if the score assigned to the group is determined by the suitability determination procedure to conform to the predetermined criteria, sets the group as a conforming group. The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons constituting the conforming group, The aforementioned category classification procedure classifies the conforming group into a predetermined category based on the attribute information. A recording medium as described in any one of the items 22 to 26 of the appendix. (Note 28) This further includes the procedure for adjusting service details, The service content adjustment procedure adjusts the service content provided to the conforming group based on the predetermined category to which the conforming group belongs. Recording medium as described in Appendix 27. [Industrial applicability]

[0106] According to this disclosure, categories can be assigned to appropriately formed groups. Therefore, this disclosure can be widely and usefully used in various fields that involve categorizing groups. [Explanation of symbols]

[0107] 10, 10A, 10B, 10C, 10D Category Classification Device 11 Time acquisition section 12. Selection of accompanying persons 13 Group formation section 14 Attribute information acquisition section 15 Category Classification Section 16 Distance acquisition part 17 Provisional Group Formation Department 18. Duplicate Target Extraction Unit 19. Score Assignment Section 20 Approval / Rejection Unit 21 Settings Section 22 Service Content Adjustment Department 101 Central Processing Unit 102 memory 103 Bus 104 Storage device 105 Input device 106 Output device 107 Communication devices

Claims

1. This includes procedures for obtaining timing, extracting accompanying persons, forming groups, obtaining attribute information, and categorizing. The aforementioned procedure for obtaining the time period involves obtaining the time period during which each subject was in a specific area, The procedure for selecting accompanying persons involves selecting from multiple persons that are in the same time period as accompanying persons, The group formation procedure involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons who constitute the group, The aforementioned category classification procedure classifies the group into a predetermined category based on the attribute information. A category classification program that causes a computer to perform each of the above steps.

2. In lieu of or in addition to the aforementioned time acquisition procedure, a distance acquisition procedure is further included: The distance acquisition procedure acquires the distance between the subjects in the specified area, The procedure for selecting accompanying persons involves selecting persons who are close in distance for a predetermined period of time or longer from among a group of persons as accompanying persons. The category classification program according to claim 1.

3. The distance acquisition procedure acquires the distance between the subjects based on position estimation. The category classification program according to claim 2.

4. The aforementioned specific area is an area included in the facility. The aforementioned specific area includes at least one of the entrance area and the exit area. The aforementioned entrance area includes an entrance area relating to the entrance to the facility and an entrance area relating to the entrance to a passage within the facility. The aforementioned exit area includes an exit area relating to an exit from the facility, and an exit area relating to an exit from a passage within the facility. A category classification program according to any one of claims 1 to 3.

5. This further includes a procedure for forming a provisional group and a procedure for identifying duplicate individuals. The aforementioned provisional group formation procedure is: If the aforementioned specific area is an entrance area related to the entrance to the facility, the group consisting of the accompanying persons shall be formed as a provisional group upon entry to the facility, and If the aforementioned specific area is an exit area related to the exit from the facility, the group consisting of the accompanying persons shall be formed as a provisional group at the time of leaving the facility. The procedure for extracting duplicate individuals involves extracting duplicate individuals who are included in both the provisional group for entering the facility and the provisional group for leaving the facility from the provisional group for entering the facility and the provisional group for leaving the facility. The group formation procedure involves forming a group consisting of the overlapping individuals as the group. The category classification program according to claim 4.

6. This further includes a scoring procedure, a suitability determination procedure, and a setting procedure. The scoring procedure, when the group is formed by the group formation procedure, assigns a score to the group corresponding to the type of the specific area. The aforementioned suitability determination procedure determines whether the score assigned to the group conforms to a predetermined standard, The setting procedure, if the score assigned to the group is determined by the suitability determination procedure to conform to the predetermined criteria, sets the group as a conforming group. The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons constituting the conforming group, The aforementioned category classification procedure classifies the conforming group into a predetermined category based on the attribute information. A category classification program according to any one of claims 1 to 3.

7. This further includes the procedure for adjusting service details, The service content adjustment procedure adjusts the service content provided to the conforming group based on the predetermined category to which the conforming group belongs. The category classification program according to claim 6.

8. It includes a timing acquisition unit, a companion target extraction unit, a group formation unit, an attribute information acquisition unit, and a category classification unit, The aforementioned time acquisition unit acquires the time period during which each subject was in a specific area, The aforementioned accompanying person extraction unit extracts from a group of aforementioned persons the persons who are in the same time period as accompanying persons, The group formation unit forms groups composed of the accompanying persons for each specific area, The attribute information acquisition unit acquires attribute information relating to the attributes of the subject persons constituting the group, The category classification unit classifies the group into a predetermined category based on the attribute information. Category classification device.

9. This includes a timing acquisition process, a process for selecting accompanying persons, a group formation process, an attribute information acquisition process, and a category classification process. The aforementioned time acquisition process acquires the time period during which each subject was in a specific area, The aforementioned process of selecting accompanying persons involves selecting from a group of persons that are in the same time period as accompanying persons, The group formation step involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition step involves acquiring attribute information relating to the attributes of the subject persons constituting the group, The category classification step involves classifying the group into a predetermined category based on the attribute information. A categorization method in which each of the above steps is performed by a computer.

10. This includes procedures for obtaining timing, extracting accompanying persons, forming groups, obtaining attribute information, and categorizing. The aforementioned procedure for obtaining the time period involves obtaining the time period during which each subject was in a specific area, The procedure for selecting accompanying persons involves selecting from multiple persons that are in the same time period as accompanying persons, The group formation procedure involves forming groups consisting of the accompanying persons for each specific area, The attribute information acquisition procedure acquires attribute information relating to the attributes of the subject persons who constitute the group, The aforementioned category classification procedure classifies the group into a predetermined category based on the attribute information. A computer-readable recording medium containing a program that causes a computer to perform each of the aforementioned steps.

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