Information processing device, method of operating the information processing device, operating program of the information processing device

Abstract

Provided are: an information processing device which can present, to an event organizer, information that would be useful for marketing the event, without any hassle; a method for operating the information processing device; and a program for operating the information processing device. A CPU of an information processing server comprises an acquisition unit, a derivation unit, and a distribution control unit. The acquisition unit acquires an image captured by a user during a targeted event in which a satisfaction level of the user is measured. On the basis of the image, the derivation unit derives the satisfaction level of the user with regard to the targeted event. The distribution control unit presents, to the target event organizer, user attributes and satisfaction level-related information pertaining to the satisfaction level.

Description

Technical Field

[0001] The technology of the present disclosure relates to an information processing apparatus, a method for operating the information processing apparatus, and an operation program for the information processing apparatus.

Background Art

[0002] Information suitable for a user is presented to the user. For example, in Patent Document 1, there is described a technique of acquiring an image taken by a user at a tourist spot, deriving the user's satisfaction with the tourist spot based on the number of images, and presenting recommended tourist spots to the user according to the derived satisfaction.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Among the organizers of various events such as tours around tourist spots or outdoor experiences such as trekking, camping, fishing, potato digging, and rice planting, there are those who conduct marketing to increase the number of users participating in the events. For such organizers conducting such marketing, information such as what attributes of users have high satisfaction is extremely important.

[0005] A conventional method for understanding user satisfaction with an event involves sending questionnaires to users and having them answer them. However, this conventional method requires the effort of sending and collecting questionnaires, as well as the effort of answering them. In this respect, the technology described in Patent Document 1, which derives satisfaction from images taken by users at tourist spots, is preferable because it eliminates the effort of sending and collecting questionnaires, as well as the effort of answering them. However, simply presenting the user satisfaction derived in the manner of Patent Document 1 to the event organizer would not be very useful to the event organizer.

[0006] One embodiment of the technology of this disclosure provides an information processing device, a method for operating the information processing device, and an operating program for the information processing device that can present event organizers with information useful for event marketing without requiring any effort. [Means for solving the problem]

[0007] The information processing device disclosed herein comprises a processor and memory connected to or embedded in the processor, wherein the processor acquires images taken by the user during a target event for which user satisfaction is measured, derives the user's satisfaction with the target event based on the images, and presents satisfaction-related information regarding the user's attributes and satisfaction to the organizer of the target event.

[0008] The processor preferably derives specific attributes from users who tend to like the event among those who participated in the event, by statistically analyzing satisfaction levels, and presents these specific attributes as satisfaction-related information.

[0009] It is preferable for the processor to give greater weight to the attributes of users with higher satisfaction levels when deriving specific attributes.

[0010] It is preferable for the processor to present, in addition to specific attributes, setting attributes, which are user attributes set by the organizer for the target event, as satisfaction-related information.

[0011] Preferably, the processor derives a first representative satisfaction level that represents the satisfaction level of all users who participated in the event, and a second representative satisfaction level that represents the satisfaction level of users who participated in the event and whose settings attributes were set by the organizer for the event. If the second representative satisfaction level is lower than the first representative satisfaction level, and the absolute value of the difference between the first and second representative satisfaction levels satisfies a pre-set threshold condition, it is preferable to present a notification to the organizer prompting them to change the settings attributes.

[0012] It is preferable for the processor to present information that associates satisfaction levels with user attributes as satisfaction-related information.

[0013] The processor preferably derives satisfaction based on conditions related to image-related evaluation values, which include at least one of the following: the number of images taken, the number of times an image is played back, and the number of images posted.

[0014] The processor preferably derives satisfaction levels based on the results of analyzing the facial expressions of the people in the image.

[0015] The processor preferably derives a satisfaction level for each of at least one of the following: the location where the image was taken and the time of day when the image was taken in the target event.

[0016] The method of operating the information processing device disclosed herein includes acquiring images taken by a user during a target event for which user satisfaction is measured, deriving the user's satisfaction level with the target event based on the images, and presenting satisfaction-related information regarding the user's attributes and satisfaction level to the organizer of the target event.

[0017] The operation program of the information processing apparatus of the present disclosure causes a computer to execute processing including acquiring an image captured by a user during a target event for measuring user satisfaction, deriving the user satisfaction with respect to the target event based on the image, and presenting satisfaction-related information regarding the user's attributes and satisfaction to the organizer of the target event.

Effect of the Invention

[0018] According to the technology of the present disclosure, it is possible to provide an information processing apparatus, an operation method of the information processing apparatus, and an operation program of the information processing apparatus that can present information useful for event marketing to the organizer of the event without much effort.

Brief Description of the Drawings

[0019] [Figure 1] It is a diagram showing an information processing system. [Figure 2] It is a diagram showing information exchanged between an information processing server, a user terminal, and an organizer terminal. [Figure 3] It is a diagram showing the inside of an event information DB and the content of event information. [Figure 4] It is a diagram showing the inside of an image DB. [Figure 5] It is a diagram showing a state where an event ID is added to the attached information of an image captured by a user during an event. [Figure 6] [[ID=3*]]It is a block diagram showing a computer constituting an information processing server and an organizer terminal. [Figure 7] It is a block diagram showing a processing unit of a CPU of an information processing server. [Figure 8] It is a diagram showing a satisfaction-related information distribution request. [Figure 9] It is a flowchart showing a procedure for deriving satisfaction-related information by a derivation unit. [Figure 10] It is a diagram showing a state where the number of captured images is converted into satisfaction using a satisfaction conversion table. [Figure 11]This diagram shows how the average satisfaction level is calculated for each user attribute, and based on that average satisfaction level, specific attributes are derived that indicate users who participated in the target event and tend to like the event. [Figure 12] This is a block diagram showing the CPU processing unit of the organizer's terminal. [Figure 13] This diagram shows an information display screen that shows specific attributes. [Figure 14] This is a flowchart showing the processing procedure of the information processing server. [Figure 15] This diagram shows how the number of times an image is viewed is converted to a satisfaction level using a satisfaction level conversion table. [Figure 16] This diagram shows how the number of images posted is converted into a satisfaction rating using a satisfaction rating conversion table. [Figure 17] This diagram illustrates a mechanism where the attributes of users with higher satisfaction levels are given greater weight when deriving specific attributes. [Figure 18] This is a diagram showing the settings attribute table. [Figure 19] This figure shows satisfaction-related information, including specific attributes and setting attributes. [Figure 20] This figure shows an information display screen that shows specific attributes and setting attributes. [Figure 21] This figure shows an overview of the processing of the second embodiment, which presents the organizer with a notification prompting them to change the setting attributes. [Figure 22] This figure shows an information display screen that shows a message prompting the organizer to change the setting attributes. [Figure 23] This figure shows satisfaction-related information, where satisfaction levels are correlated with user attributes. [Figure 24] This diagram shows how the facial expressions of people in an image are analyzed by the analysis unit, and how the facial expression analysis results are output from the analysis unit to the derivation unit. [Figure 25] This diagram shows how satisfaction levels are adjusted based on the number of images in which facial expression analysis results showed a smile, and the satisfaction level adjustment conditions, derived from the number of images taken. [Figure 26]This figure shows an overview of the processing of the 4_1 embodiment, which derives satisfaction levels for each location where an image was taken in the target event. [Figure 27] This figure shows an overview of the processing of the 4_2 embodiment, which derives satisfaction levels for each time period during which images were taken at the target event. [Figure 28] This is a diagram showing user movement path information. [Figure 29] This is a diagram showing user gathering and dispersal information. [Figure 30] This diagram shows an overview of the process for deriving trend information and the trend information itself. [Modes for carrying out the invention]

[0020] As an example, as shown in Figure 1, the information processing system 2 comprises an information processing server 10, multiple user terminals 11, and multiple organizer terminals 12. The information processing server 10, user terminals 11, and organizer terminals 12 are interconnected via a network 13, enabling mutual communication. The network 13 is a Wide Area Network (WAN), such as the Internet or a public telecommunications network.

[0021] The information processing server 10 is, for example, a server computer, a workstation, etc., and is an example of an "information processing device" related to the technology disclosed herein. The user terminal 11 is a terminal owned by each user 14. The user terminal 11 has at least the function of playing back and displaying an image 24 (see Figure 2, etc.) and the function of transmitting the image 24 to the information processing server 10. The user terminal 11 is, for example, a smartphone, a tablet terminal, and a personal computer, etc.

[0022] The organizer terminal 12 is a terminal operated by the event organizer 15. The organizer terminal 12 is, for example, a desktop personal computer. Events include, for example, tours of tourist spots, tours of theme parks, agricultural experiences, craft experiences, lifelong learning experiences, and stamp rallies. The organizer 15 is, for example, an employee or staff member of a travel agency, event planning company, or local government.

[0023] As an example, as shown in Figure 2, the information processing server 10 is connected to an event information database (hereinafter abbreviated as DB (Data Base)) server 20 and an image DB server 21 via a network such as a LAN (Local Area Network) (not shown). The information processing server 10 receives event information 22 entered by the event organizer 15 through the organizer terminal 12. Then, it transmits the received event information 22 to the event information DB server 20. The event information DB server 20 has an event information DB 23. The event information DB server 20 stores and manages the event information 22 from the information processing server 10 in the event information DB 23.

[0024] The information processing server 10 receives a search request (not shown) for event information 22 from the user terminal 11 and forwards the search request to the event information DB server 20. The search request for event information 22 includes search keywords for the event desired by the user 14. The search keywords are, for example, the category 30 of each event (see Figure 3), the date, and the location. The event information DB server 20 searches the event information DB 23 for event information 22 corresponding to the forwarded search request and sends the retrieved event information 22 to the information processing server 10. The information processing server 10 delivers the event information 22 from the event information DB server 20 to the user terminal 11 that sent the search request.

[0025] User 14 views event information 22 distributed from the information processing server 10 via user terminal 11. User 14 operates user terminal 11 to select the event information 22 of the event they wish to participate in from among the event information 22 distributed from the information processing server 10. Then, they apply to participate in the event of the selected event information 22.

[0026] The information processing server 10 receives an image 24 from the user terminal 11 and sends the received image 24 to the image DB server 21. The image DB server 21 has an image DB 25. The image DB server 21 stores and manages the image 24 from the information processing server 10 in the image DB 25. In addition, the image DB server 21 sends the image 24 stored in the image DB 25 to the information processing server 10 in response to a request from the information processing server 10.

[0027] Furthermore, the information processing server 10 distributes satisfaction-related information 26 to the organizer terminal 12. The satisfaction-related information 26, as will be described in more detail later, is information regarding the attributes of the user 14 and the user 14's satisfaction with the target event.

[0028] As an example, as shown in Figure 3, the event information DB23 is divided into multiple categories 30, and multiple event information items 22 are stored in each category 30. Category 30 is a broad classification of events such as "agricultural experiences" and "stamp rallies." In addition to these, Category 30 also includes "tours visiting tourist spots," "tours to play at theme parks," "craft experiences," and "lifelong learning experiences."

[0029] Event information 22 includes basic information 32 and applicant user information 33, etc. Basic information 32 includes an event ID (Identification Data) to uniquely identify the event, name, date, and location. The event ID is automatically assigned by the event information DB server 20 when the event information 22 is first stored in the event information DB 23. Applicant user information 33 contains the user IDs of users 14 who applied to participate in the event through the user terminal 11, such as "U0001" and "U0010".

[0030] As an example, as shown in Figure 4, the image database 25 contains multiple image folders 35. Each image folder 35 is assigned to a specific user 14, making it unique to each user 14. Therefore, there are as many image folders 35 as there are users 14. Each image folder 35 is associated with a user ID.

[0031] The image folder 35 stores the images 24 owned by user 14. The images 24 owned by user 14 include images taken by user 14 using the camera function of user terminal 11. In addition, the images 24 owned by user 14 also include images taken using digital cameras other than user terminal 11. Furthermore, the images 24 owned by user 14 also include images received by user 14 from other users 14 such as friends and family, images downloaded by user 14 from the internet, and images scanned by user 14. The images 24 in the image folder 35 are periodically synchronized with the images 24 stored locally on user terminal 11.

[0032] Each image 24 has accompanying information 36. The accompanying information 36 includes the user ID of the user 14 who took the image 24, the date and time the image 24 was taken, and the location where it was taken (see Figure 5). The location where it was taken is determined from the latitude and longitude information obtained by the GPS (Global Positioning System) function built into the user terminal 11 or the digital camera.

[0033] The image folder 35 is associated with user 14's attribute information 37. Attribute information 37 is registered by user 14. Attribute information 37 includes user 14's date of birth, gender, residential area, and family structure. The residential area is a combination of prefecture and city / ward / town / village. For family structure, children are registered with categories such as kindergarten child or elementary school student. Note that attribute information 37 may be stored in a separate database from image DB 25.

[0034] User 14 participates in an event they have registered for. During the event, they take images 24 using the camera function of their user terminal 11. Figure 5 shows an example of an image 24 taken by user 14 during the event.

[0035] In Figure 5, the information processing server 10 first queries the event information DB server 20 to see if the user ID of user 14 (referred to as the "shooting user" in Figure 5) who took the image 24 is registered in the application user information 33 as event information 22. If the user ID of user 14 who took the image 24 is registered in the application user information 33 as event information 22, the information processing server 10 compares the date of the event with the date and time the image 24 was taken, and the location of the event with the location where the image 24 was taken. If the date and time and the location match, the information processing server 10 determines that the image 24 was taken by user 14 during the event. The information processing server 10 adds the event ID to the supplementary information 36 of the image 24 that it determined was taken by user 14 during the event. Therefore, it is possible to distinguish whether or not the image 24 was taken by user 14 during the event based on whether or not the event ID is registered in the supplementary information 36. Alternatively, the user 14 may manually enter that the image 24 was taken during the event, for example, by registering the event name as a tag in supplementary information 36.

[0036] As an example, as shown in Figure 6, the computers comprising the information processing server 10 and the organizer terminal 12 have basically the same configuration and include storage 40, memory 41, CPU (Central Processing Unit) 42, communication unit 43, display 44, and input device 45. These are interconnected via a bus line 46.

[0037] Storage 40 is a hard disk drive built into the computers constituting the information processing server 10 and the organizer terminal 12, or connected via cable or network. Alternatively, storage 40 is a disk array consisting of multiple hard disk drives installed in series. Storage 40 stores control programs such as the operating system, various application programs (hereinafter abbreviated as AP (Application Program)), and various data associated with these programs. A solid-state drive may be used instead of a hard disk drive.

[0038] Memory 41 is work memory for the CPU 42 to execute processing. The CPU 42 loads programs stored in storage 40 into memory 41 and executes processing according to the programs. In this way, the CPU 42 comprehensively controls each part of the computer. CPU 42 is an example of a "processor" related to the technology of this disclosure. Note that memory 41 may be built into the CPU 42.

[0039] The communication unit 43 is a network interface that controls the transmission of various types of information via the network 13, etc. The display 44 displays various screens. These screens are equipped with GUI (Graphical User Interface) operation functions. The computers constituting the information processing server 10 and the organizer terminal 12 receive operation instructions from the input devices 45 through the various screens. The input devices 45 include keyboards, mice, and touch panels.

[0040] In the following explanation, each component of the computer constituting the information processing server 10 will be denoted by the subscript "A," and each component of the computer constituting the organizer terminal 12 will be denoted by the subscript "B" to distinguish them.

[0041] As an example, as shown in Figure 7, the storage 40A of the information processing server 10 stores an operating program 50. The operating program 50 is an application program (AP) that causes the computers constituting the information processing server 10 to function as an "information processing device" according to the technology of this disclosure. In other words, the operating program 50 is an example of an "operating program for an information processing device" according to the technology of this disclosure. The storage 40A also stores a satisfaction conversion table 51.

[0042] When the operating program 50 is started, the CPU 42A of the information processing server 10 works in cooperation with the memory 41 and other components to function as a request receiving unit 55, an acquisition unit 56, an output unit 57, and a distribution control unit 58.

[0043] The request receiving unit 55 receives various requests from the organizer terminal 12. For example, the request receiving unit 55 receives a satisfaction-related information distribution request 60. As an example, as shown in Figure 8, the satisfaction-related information distribution request 60 includes an event ID and an organizer terminal ID. The event ID is the ID of the event in which the organizer 15 wants to measure the satisfaction of the user 14, i.e., the "target event" related to the technology of this disclosure. The organizer terminal ID is the ID of the organizer terminal 12 that sent the satisfaction-related information distribution request 60. The request receiving unit 55 outputs the event ID from the satisfaction-related information distribution request 60 to the acquisition unit 56. The request receiving unit 55 also outputs the organizer terminal ID from the satisfaction-related information distribution request 60 to the distribution control unit 58.

[0044] Returning to Figure 7, when the event ID of the target event is entered from the request reception unit 55, the acquisition unit 56 sends an acquisition request 61 to the image DB server 21. The acquisition request 61 is a copy of the event ID of the target event and requests the image 24 in which the event ID of the target event is registered in the supplementary information 36. The image 24 in which the event ID of the target event is registered in the supplementary information 36 is none other than the image 24 taken by user 14 during the target event. The acquisition request 61 also requests the attribute information 37 of user 14 who took the image 24 in which the event ID of the target event is registered in the supplementary information 36.

[0045] The image database server 21 reads the image 24 and attribute information 37 from the image database 25 in response to the acquisition request 61, and transmits the read image 24 and attribute information 37 to the information processing server 10. The acquisition unit 56 acquires the image 24 and attribute information 37 transmitted from the image database server 21 in response to the acquisition request 61. The acquisition unit 56 outputs the acquired image 24 and attribute information 37 to the derivation unit 57.

[0046] The derivation unit 57 derives the user 14's satisfaction level for the target event based on the image 24 from the acquisition unit 56, while referring to the satisfaction level conversion table 51. The derivation unit 57 generates attribute information 37 from the acquisition unit 56 and satisfaction-related information 26 based on the derived satisfaction level. The derivation unit 57 outputs the generated satisfaction-related information 26 to the distribution control unit 58.

[0047] The distribution control unit 58 controls the distribution of satisfaction-related information 26 from the derivation unit 57 to the organizer terminal 12, the source of the satisfaction-related information distribution request 60. At this time, the distribution control unit 58 identifies the organizer terminal 12, the source of the satisfaction-related information distribution request 60, based on the organizer terminal ID of the satisfaction-related information distribution request 60 from the request reception unit 55. In this example, by distributing the satisfaction-related information 26 to the organizer terminal 12 in this way, the satisfaction-related information 26 is presented to the organizer 15.

[0048] Figure 9 is a flowchart showing an example of the procedure for deriving satisfaction-related information 26 by the derivation unit 57. Figures 10 and 11 are explanatory diagrams showing an example of the procedure for deriving satisfaction-related information 26 by the derivation unit 57.

[0049] First, the derivation unit 57 aggregates the number of images 24 taken during the target event for each user 14, as shown in Table 65 of Figure 10 (step ST1301). The derivation unit 57 then converts the aggregated number of images taken into satisfaction levels using the satisfaction level conversion table 51, as shown in Table 66 (step ST1302). The number of images taken is an example of an "image-related evaluation value" related to the technology of this disclosure.

[0050] The satisfaction conversion table 51 is a table that registers satisfaction levels in relation to the number of images 24 taken during the target event. In Figure 10, satisfaction levels of 1 are registered for 1 to 5 images, 2 for 6 to 10 images, ..., 4 for 16 to 20 images, and 5 for 21 or more images. A higher satisfaction level indicates that the user 14 is more satisfied with the target event. The reason for setting higher satisfaction levels for a larger number of images taken is based on the assumption that users 14 who are satisfied with the target event will take many images 24. The satisfaction conversion table 51 is an example of the "conditions related to image-related evaluation values" related to the technology disclosed herein.

[0051] Next, the derivation unit 57 calculates the average satisfaction level for each attribute of the user 14, as shown in Tables 68A, 68B, 68C, and 68D in Figure 11 (step ST1303). Specifically, the derivation unit 57 calculates the average satisfaction level for each gender of the user 14, as shown in Table 68A. The derivation unit 57 also calculates the average satisfaction level for each age group of the user 14, as shown in Table 68B. Age groups include teenagers, people in their 30s, and people in their 60s, etc. The derivation unit 57 also calculates the average satisfaction level for each residential area (region) of the user 14, as shown in Table 68C. Residential areas include Hokkaido / Tohoku, Tokai / Hokuriku, and Kyushu / Okinawa, etc. Furthermore, the derivation unit 57 calculates the average satisfaction level for each family structure of the user 14, as shown in Table 68D. Family structures include single people and people with children (elementary school age or younger), etc.

[0052] The derivation unit 57 derives specific attributes, which are the attributes of users 14 who tend to like the target event, based on the calculated average satisfaction level (step ST1304). Specifically, as shown in Figure 11, the derivation unit 57 derives gender with a relatively high average satisfaction level as a specific attribute. The derivation unit 57 also derives the age group with the first and second highest average satisfaction level, the residential area with the first and second highest average satisfaction level, and the family structure with the first and second highest average satisfaction level as specific attributes. Figure 11 shows an example where male is derived as gender, 50s and 60s as age group, Shikoku and Chugoku as residential area, and single and married as family structure. The derivation unit 57 outputs the derived specific attributes as satisfaction-related information 26 to the distribution control unit 58 (step ST1305).

[0053] As an example, as shown in Figure 12, the storage 40B of the organizer terminal 12 stores the marketing AP 75. The CPU 42B of the organizer terminal 12 works in cooperation with the memory 41 and other components to function as a browser control unit 80. The browser control unit 80 controls the operation of the web browser dedicated to the marketing AP 75.

[0054] The browser control unit 80 receives various operation instructions from the organizer 15 via the input device 45B through various screens. The browser control unit 80 sends various requests to the information processing server 10 in response to the operation instructions. For example, in response to an instruction to distribute satisfaction-related information 26, the browser control unit 80 sends a satisfaction-related information distribution request 60 to the information processing server 10.

[0055] The browser control unit 80 generates various screens, such as the information display screen 85 (see Figure 13), based on satisfaction-related information 26 from the information processing server 10. The browser control unit 80 outputs the generated screens to the display 44B.

[0056] Figure 13 shows an example of an information display screen 85 displayed on the display 44B of the organizer terminal 12. The information display screen 85 displays the name of the target event for which the distribution of satisfaction-related information 26 was requested. In addition, the information display screen 85 displays specific attributes as satisfaction-related information 26, as indicated by the dashed-dot line enclosure and symbol 86. In Figure 13, "Fuji Five Lakes Cherry Blossom Viewing Tour" is used as an example of the target event. Also, as with the example shown in Figure 11, male, 50s and 60s, Shikoku and Chugoku, single and married are used as examples of specific attributes. The information display screen 85 is turned off when the confirmation button 87 is selected.

[0057] Next, the operation of the above configuration will be explained with reference to the flowchart shown in Figure 14 as an example. The CPU 42A of the information processing server 10 functions as a request receiving unit 55, an acquisition unit 56, an output unit 57, and a distribution control unit 58, as shown in Figure 7. In addition, the CPU 42B of the organizer terminal 12 functions as a browser control unit 80, as shown in Figure 12.

[0058] The organizer 15 instructs the organizer terminal 12, through its input device 45B, to distribute satisfaction-related information 26 related to the event for which user 14 satisfaction is to be measured, i.e., the target event. As a result, the browser control unit 80 sends a satisfaction-related information distribution request 60 to the information processing server 10.

[0059] The satisfaction-related information distribution request 60 from the organizer terminal 12 is received by the request reception unit 55 of the information processing server 10 (YES in step ST100). As shown in Figure 8, the event ID of the target event of the satisfaction-related information distribution request 60 is output from the request reception unit 55 to the acquisition unit 56. In addition, the organizer terminal ID of the satisfaction-related information distribution request 60 is output from the request reception unit 55 to the distribution control unit 58.

[0060] An acquisition request 61 is sent from the acquisition unit 56 to the image DB server 21 requesting an image 24 taken by user 14 during the target event, and attribute information 37 of user 14 who took the image (step ST110). The image DB server 21 reads the image 24 and attribute information 37 corresponding to the acquisition request 61 from the image DB 25 and sends them to the information processing server 10. The image 24 and attribute information 37 corresponding to the acquisition request 61 are acquired by the acquisition unit 56 (step ST120).

[0061] As shown in Figures 9 to 11, the derivation unit 57 derives the user 14's satisfaction level with the target event based on the image 24. Then, attribute information 37 and satisfaction-related information 26 based on the satisfaction level are derived (step ST130). In this example, the satisfaction-related information 26 is a specific attribute of the user 14 who participated in the target event and tend to like the target event. The satisfaction-related information 26 is output from the derivation unit 57 to the distribution control unit 58. The satisfaction-related information 26 is then distributed by the distribution control unit 58 to the organizer terminal 12, the source of the satisfaction-related information distribution request 60 (step ST140).

[0062] On the organizer's terminal 12, the browser control unit 80 outputs the information display screen 85 shown in Figure 13 to the display 44B. This makes the satisfaction-related information 26 available for viewing by the organizer 15.

[0063] As described above, the CPU 42A of the information processing server 10 includes an acquisition unit 56, a derivation unit 57, and a distribution control unit 58. The acquisition unit 56 acquires images 24 taken by the user 14 during the target event for which the user 14's satisfaction level is to be measured. The derivation unit 57 derives the user 14's satisfaction level with the target event based on the images 24. The distribution control unit 58 presents the satisfaction-related information 26 regarding the user 14's attributes and satisfaction level to the event organizer 15's organizer terminal 12. Therefore, it is possible to present information useful for event marketing to the event organizer 15 without requiring any effort. As a result, the organizer 15 can recommend the event to the user 14 under an appropriate marketing strategy. This is also preferable for the user 14, as it increases the likelihood of being recommended an event that suits their attributes.

[0064] The derivation unit 57 derives specific attributes, which are the attributes of users 14 who tend to like the target event, by statistically analyzing satisfaction levels. The distribution control unit 58 presents these specific attributes as satisfaction-related information 26. This allows the organizer 15 to know which users 14 should be the main target of the event. The organizer 15 can then implement effective measures to increase the number of users 14 participating in the event, such as tailoring the content of the event's commercials to users 14 with specific attributes, or limiting the users 14 providing the event's commercials to users 14 with specific attributes.

[0065] The derivation unit 57 derives satisfaction levels based on the satisfaction conversion table 51, which contains conditions related to the number of images 24 taken. Therefore, satisfaction levels can be derived through a relatively simple process: the number of images 24 taken is aggregated for each user 14 who participated in the target event, and the aggregated number of images taken is converted into satisfaction levels using the satisfaction conversion table 51.

[0066] Image-related evaluation values ​​are not limited to the number of images 24 taken during the example target event. As an example, as shown in Figure 15, the number of times the images 24 taken during the target event are played back may be used as the image-related evaluation value. In this case, the information processing server 10 receives the number of times the user 14 played back and displayed the images 24 taken during the target event from a device with the function of playing back and displaying images 24, such as a user terminal 11.

[0067] The derivation unit 57 uses a satisfaction conversion table 90 in which satisfaction levels are registered for the number of times images 24 taken during the target event are played. In Figure 15, satisfaction level 1 is registered for 0 to 2 plays, satisfaction level 2 for 3 and 4 plays, ..., satisfaction level 4 for 7 and 8 plays, and satisfaction level 5 for 9 or more plays. The reason for setting higher satisfaction levels for higher play counts is based on the assumption that users 14 who are satisfied with the target event will play and display the images 24 taken during the target event many times. The satisfaction conversion table 90 is an example of the "conditions related to image-related evaluation values" related to the technology of this disclosure.

[0068] As shown in Table 91, the derivation unit 57 calculates the number of times each image 24 taken during the target event is played for each user 14. For example, the derivation unit 57 calculates the number of times each image 24 taken during the target event is played for each user 14 on the user terminal 11, etc., over a period of three months from the target event, and rounds the average of the number of times the user 14 played the image 24 on the user terminal 11, etc., to the nearest whole number. If there are three images 24 taken during the target event, and the first image is played 4 times, the second image is played 6 times, and the third image is played 3 times, the average of the number of plays is (4+6+3) / 3 ≈ 4.3, so the number of times each image 24 taken during the target event is played is 4.

[0069] As shown in Table 92, the derivation unit 57 converts the calculated number of plays into a satisfaction level using the satisfaction level conversion table 90. The subsequent processing is the same as in the case where the number of shots is used as the image-related evaluation value, so the explanation is omitted.

[0070] Thus, in this embodiment, satisfaction is derived based on the satisfaction conversion table 90, which is a condition related to the number of times image 24 is played. Therefore, similar to the embodiment in which the number of images taken is used as an image-related evaluation value, satisfaction can be derived with a relatively simple process.

[0071] As an example, as shown in Figure 16, the number of images 24 taken during the target event may also be used as an image-related evaluation value. The number of images 24 taken during the target event may be posted by user 14 to an unspecified number of third parties via an image posting SNS (Social Networking Service), etc. In this case, the information processing server 10 receives the number of images 24 taken during the target event that user 14 has posted to an image posting SNS, etc., from a device such as a user terminal 11 that has the function of posting images 24 to an image posting SNS, etc.

[0072] The derivation unit 57 uses a satisfaction conversion table 95 in which satisfaction levels are registered for the number of images 24 taken during the target event that are posted. In Figure 16, a satisfaction level of 1 is registered for 0 posts, 2 for 1 and 2 posts, ..., 4 for 5 and 6 posts, and 5 for 7 or more posts. The reason for setting higher satisfaction levels for a larger number of posts is based on the assumption that users 14 who are satisfied with the target event will post many images 24 taken during the event to image posting SNS etc. The satisfaction conversion table 95 is an example of the "conditions related to image-related evaluation values" related to the technology disclosed herein.

[0073] As shown in Table 96, the derivation unit 57 aggregates the number of images 24 posted by each user 14 during the target event. For example, the derivation unit 57 aggregates the number of images 24 posted by user 14 to an image posting SNS, etc., using a user terminal 11, etc., within one week from the target event.

[0074] The derivation unit 57 converts the aggregated number of posts into a satisfaction level using the satisfaction level conversion table 95, as shown in Table 97. The subsequent processing is the same as in the case where the number of photos taken is used as the image-related evaluation value, so the explanation is omitted.

[0075] Thus, in this embodiment, satisfaction is derived based on the satisfaction conversion table 95, which is a condition related to the number of images posted (image 24). Therefore, similar to embodiments that use the number of images taken as an image-related evaluation value, satisfaction can be derived with relatively simple processing.

[0076] Satisfaction levels may be derived based on conditions relating to at least two of the following: the number of photos taken of Image 24, the number of views, and the number of posts. For example, the total number of photos taken of Image 24 and the number of views, the number of views of Image 24 and the number of posts, or the number of photos taken of Image 24, the number of views, and the number of posts. In the case of the number of photos taken of Image 24 and the number of views, for example, the sum of the number of photos taken of Image 24 and the number of views is calculated, and the total is converted to a satisfaction level using a satisfaction conversion table in which satisfaction levels for the total are registered.

[0077] As an example, as shown in Figure 17, satisfaction may be taken into account when deriving specific attributes. In Figure 17, the derivation unit 57 uses the weighting coefficient table 100 when calculating the age of a specific attribute. The weighting coefficient table 100 is stored in storage 40A.

[0078] First, the derivation unit 57 derives the satisfaction level for each user 14, as shown in Table 101. The derivation unit 57 multiplies the age of each user 14 by a weighting coefficient corresponding to the satisfaction level and adds them together. By dividing this by the number of users 14, the weighted average of the ages of each user 14 is obtained, and this weighted average is used as the age for a specific attribute.

[0079] Figure 17 illustrates the case where a weighting coefficient of 1 is set for satisfaction levels 1-3, and a weighting coefficient of 1.5 is set for satisfaction levels 4 and 5. Furthermore, Figure 17 illustrates the case where a weighting coefficient of 1.5 is multiplied for the age of user ID "U0030" (age 40) with satisfaction level 5, and for user ID "U0035" (age 50) with satisfaction level 4. In this case, the simple average age of each of the 14 users is (20+30+40+50) / 4 = 35, but the weighted average is (20+30+40×1.5+50×1.5) / 4 ≈ 46.

[0080] Thus, in this embodiment, the derivation unit 57 gives greater weight to the attributes of users 14 with higher satisfaction levels when deriving specific attributes. Therefore, it is possible to derive specific attributes that are aligned with the attributes of users 14 with high satisfaction levels.

[0081] Other attributes besides age can also be derived using weighted averages. For example, in the case of gender, males can be assigned a numerical value of 1, females 2, and so on, and the weighted average can be calculated.

[0082] [Second_1 Embodiment] As an example, as shown in Figure 18, in the second-first embodiment, the setting attribute table 105 is stored in the storage 40A. The setting attribute table 105 registers setting attributes for each event ID. Setting attributes are, for example, the attributes of the user 14 that the organizer 15 has set as the main target of the event. Like specific attributes, setting attributes include items such as the user 14's gender, age group, residential area (region), and family structure. Alternatively, setting attributes may be stored in the event information 22.

[0083] As an example, as shown in Figure 19, the derivation unit 57 generates satisfaction-related information 107 by adding set attributes to specific attributes. In Figure 19, an example is shown in which the specific attributes derived are male as gender, 30s and 40s as age, Kanto / Koshinetsu and Kinki as residential area, and married couple and with children (elementary school age or younger) as family structure. Also in Figure 19, an example is shown in which the set attributes are male as gender, 30s as age, Kinki as residential area, and with children (elementary school age or younger).

[0084] Upon receiving satisfaction-related information 107, the browser control unit 80 of the organizer terminal 12 outputs an information display screen 110, as shown in Figure 20 as an example, to the display 44B. The information display screen 110 displays specific attributes indicated by a dashed-dot line and code 86, as well as setting attributes indicated by a dashed-dot line and code 111. In Figure 20, "Rice Planting Experience Tour" is used as an example of the target event. The same examples as in Figure 19 are shown for the specific attributes and setting attributes. The information display screen 110 is turned off when the confirmation button 112 is selected.

[0085] Thus, in the second-first embodiment, the derivation unit 57 presents, in addition to the specific attributes, the setting attributes, which are the user attributes 14 set by the organizer 15 for the target event, as satisfaction-related information 107. Therefore, as shown in the information display screen 110 in Figure 20, the organizer 15 can compare the specific attributes and the setting attributes. If the specific attributes and the setting attributes are nearly identical, as in this example, the organizer 15 can confirm that their settings were correct. Conversely, if the specific attributes and the setting attributes are different, the organizer 15 can reconsider the setting attributes. As a result, effective measures can be taken to increase the number of users 14 participating in the target event.

[0086] [Second Embodiment] In the second embodiment, as in the first embodiment, the setting attribute table 105 is stored in the storage 40A. Then, as shown in Figure 21 as an example, the derivation unit 57 derives the satisfaction level of all users 14 who participated in the target event, as shown in Table 120. The derivation unit 57 also extracts users 14 from among the users 14 who participated in the target event who meet the setting attributes set by the organizer 15 for the target event, as shown in Table 121, and also extracts their satisfaction level. Specifically, users 14 who meet the setting attributes are users 14 whose gender, age group, residential area, and family structure all match the setting attributes. The setting attributes are, as in the first embodiment, for example, the attributes of users 14 that the organizer 15 assumed to be the main target of the event.

[0087] The derivation unit 57 calculates a first average satisfaction level, which is the average satisfaction level of all 14 users who participated in the target event. The derivation unit 57 also calculates a second average satisfaction level, which is the average satisfaction level of the 14 users with the specified attributes. The first average satisfaction level is an example of the "first representative satisfaction level" related to the technology of this disclosure. The second average satisfaction level is an example of the "second representative satisfaction level" related to the technology of this disclosure. The mode of the satisfaction levels of all 14 users who participated in the target event may be used as the first representative satisfaction level. Similarly, the mode of the satisfaction levels of the 14 users with the specified attributes may be used as the second representative satisfaction level.

[0088] The distribution control unit 58 distributes a change recommendation notification 123 to the organizer terminal 12 of the event organizer 15 if the first average satisfaction level and the second average satisfaction level meet the pre-set notification conditions 122. The notification conditions 122 are that the second average satisfaction level is lower than the first average satisfaction level (second average satisfaction level < first average satisfaction level), and the absolute value of the difference between the first average satisfaction level and the second average satisfaction level is greater than the pre-set threshold of 1.0 (|first average satisfaction level - second average satisfaction level|>1.0). The change recommendation notification 123 is a notification that prompts a change in the setting attributes and includes the first average satisfaction level and the second average satisfaction level. Figure 21 illustrates the case where the first average satisfaction level is 3.7 and the second average satisfaction level is 2.4, and the notification conditions 122 are met. Note that |first average satisfaction level - second average satisfaction level|>1.0 is an example of a "threshold condition" related to the technology of this disclosure.

[0089] Upon receiving the change recommendation notification 123, the browser control unit 80 of the organizer terminal 12 outputs an information display screen 130, as shown in Figure 22, to the display 44B. The information display screen 130 displays the name of the target event, the first average satisfaction level, and the second average satisfaction level. The information display screen 130 also displays a message prompting the organizer 15 to change the setting attributes. The information display screen 130 is dismissed when the confirmation button 131 is selected.

[0090] Thus, in the second embodiment, the derivation unit 57 derives a first average satisfaction level as a first representative satisfaction level that represents the satisfaction level of all users 14 who participated in the target event. The derivation unit 57 also derives a second average satisfaction level as a second representative satisfaction level that represents the satisfaction level of users 14 who participated in the target event and whose setting attributes were set by the organizer 15 for the target event. If the distribution control unit 58 finds that the second average satisfaction level is lower than the first average satisfaction level, and the absolute value of the difference between the first and second average satisfaction levels satisfies a preset threshold condition, it presents the organizer 15 with a change recommendation notification 123 prompting them to change the setting attributes.

[0091] If the second average satisfaction level is lower than the first average satisfaction level, and the absolute value of the difference between the first and second average satisfaction levels satisfies a pre-set threshold condition, it indicates a significant discrepancy between the attribute settings set by the organizer 15 and the attributes of the users 14 who actually participated in the event. Therefore, by strongly urging the organizer 15 to reconsider the attribute settings that are significantly out of touch with reality through the change recommendation notification 123, it is possible to create an opportunity for the organizer 15 to make a major shift in its marketing strategy in order to increase the number of users 14 who participate in the event.

[0092] The configured attributes can be any attributes of user 14 set by organizer 15, and are not limited to the attributes of user 14 that organizer 15 assumed to be the main target of the event.

[0093] Furthermore, satisfaction-related information is not limited to specific attributes, or specific attributes and configured attributes. As an example, as shown in Figure 23, information that associates satisfaction levels with user 14 attributes may be presented as satisfaction-related information 135. In this case, the derivation of specific attributes, etc., can be performed on the organizer terminal 12 that receives the satisfaction-related information 135. This eliminates the need to perform the derivation of specific attributes, etc., thus reducing the processing load on the information processing server 10.

[0094] The system may be configured to allow users to select which of the following to deliver: satisfaction-related information 26 for specific attributes, satisfaction-related information 107 for specific attributes and setting attributes, and satisfaction-related information 135 in which satisfaction levels are associated with user attributes 14.

[0095] [Third Embodiment] As an example, as shown in Figure 24, the CPU 42A of the information processing server 10 in the third embodiment functions as an analysis unit 140 in addition to the request receiving unit 55, acquisition unit 56, derivation unit 57, and distribution control unit 58 of the first embodiment. The analysis unit 140 analyzes whether the facial expression of an image 24 containing a person's face is a smile or not. The analysis unit 140 outputs the facial expression analysis result 141, which is the result of the analysis, to the derivation unit 57. Figure 24 illustrates the case where the facial expression is analyzed to be a smile.

[0096] As an example, as shown in Figure 25, the derivation unit 57 derives satisfaction based on the number of images 24 taken, as in the first embodiment described above. The derivation unit 57 also counts the number of images 24 taken during the target event in which the facial expression analysis result 141 was a smile, for each user 14. Then, based on the number of images 24 in which the facial expression analysis result 141 was a smile and the pre-set satisfaction adjustment conditions 145, the derivation unit 57 adds or subtracts the satisfaction derived from the number of images 24 taken.

[0097] The satisfaction adjustment conditions 145 are stored in storage 40A. For example, satisfaction adjustment condition 145 is to subtract 1 from the satisfaction level if the number of images 24 in which the facial expression analysis result 141 was a smile is 0. Also, for example, satisfaction adjustment condition 145 is to not adjust the satisfaction level if the number of images 24 in which the facial expression analysis result 141 was a smile is between 1 and 5. Furthermore, satisfaction adjustment condition 145 is to add 1 to the satisfaction level if the number of images 24 in which the facial expression analysis result 141 was a smile is 6 or more.

[0098] Figure 25 illustrates a case where the number of images 24 in which the facial expression analysis result 141 showed a smile was 8, and the satisfaction level derived based on the number of images 24 taken was 3. In this case, since the number of images 24 in which the facial expression analysis result 141 showed a smile is 6 or more, the derivation unit 57 adds 1 to the satisfaction level of 3 derived based on the number of images 24 taken, making the satisfaction level 4.

[0099] If the satisfaction level derived from the number of images 24 taken is the lowest possible, which is 1, and the number of images 24 in which the facial expression analysis result 141 showed a smile is 0, then the satisfaction level remains 1 without subtracting 1. Also, if the satisfaction level derived from the number of images 24 taken is the highest possible, which is 5, and the number of images 24 in which the facial expression analysis result 141 showed a smile is 6 or more, then the satisfaction level remains 5 without adding 1. Of course, in the former case, you could subtract 1 from the satisfaction level to make it 0, or in the latter case, you could add 1 to make it 6.

[0100] Thus, in the third embodiment, the derivation unit 57 derives satisfaction based on the facial expression analysis result 141, which is the result of analyzing the facial expression of the person in the image 24. Since satisfaction is derived from the facial expression of the person, which clearly shows whether or not they are enjoying the event, the reliability of the satisfaction level can be increased.

[0101] In Figure 25, an example is shown in which the satisfaction level derived from the number of images 24 taken is added or subtracted based on the number of images 24 in which the facial expression analysis result 141 was a smile, and the pre-set satisfaction level adjustment condition 145. However, this is not the only example. As shown in Figure 15, the satisfaction level is derived from the number of views of image 24, or as shown in Figure 16, the posting of image 24. Number of sheets The satisfaction level derived from this may be added or subtracted. Alternatively, the satisfaction level may be directly converted to the satisfaction level using a satisfaction level conversion table in which the satisfaction level corresponding to the number of images 24 in which the facial expression analysis result 141 was a smile is registered.

[0102] [Embodiment 4_1] As an example, as shown in Table 150 of Figure 26, in the 4_1 embodiment, the derivation unit 57 derives satisfaction levels for each user 14 for each location where an image 24 was taken at the target event. The derivation unit 57 generates satisfaction-related information 151 for each shooting location. As mentioned above, the shooting location is determined from the latitude and longitude information obtained by the GPS function built into the user terminal 11 or digital camera that took the image 24. The shooting locations from which satisfaction levels are derived are predetermined by the organizer 15.

[0103] The derivation unit 57 calculates image-related evaluation values ​​such as the number of photos taken for each shooting location as a preprocessing step for deriving satisfaction levels for each shooting location. Then, it converts the calculated image-related evaluation values ​​into satisfaction levels using a satisfaction level conversion table. The satisfaction level-related information 151 may consist of only specific attributes, specific attributes and setting attributes, or information that associates satisfaction levels with user 14 attributes.

[0104] Figure 26 shows an example of deriving satisfaction levels for three shooting locations, A, B, and C. It also shows an example of generating satisfaction-related information 151A for shooting location A, 151B for shooting location B, and 151C for shooting location C.

[0105] Thus, in the 4_1 embodiment, satisfaction levels are derived for each location where an image 24 was taken at the target event. This allows for the generation of satisfaction-related information 151 for each location. The organizer 15 can use this satisfaction-related information 151 to find out what kind of user 14 has high satisfaction levels at each location. For example, if the target event is a tour to a theme park and the locations where the images were taken are the attractions at the theme park, the organizer can find out which attractions are popular with which types of users 14.

[0106] [Embodiment 4_2] As an example, as shown in Table 155 of Figure 27, in the 4_2 embodiment, the derivation unit 57 derives satisfaction levels for each user 14 for each time period in which the image 24 was taken at the target event. The derivation unit 57 generates satisfaction-related information 156 for each time period in which the image was taken. The time period in which the image was taken is determined from the date and time of the image 24 in the accompanying information 36, as described above. The time periods in which satisfaction levels are derived are predetermined by the organizer 15.

[0107] Similar to the 4_1 embodiment described above, the derivation unit 57 obtains image-related evaluation values ​​such as the number of images taken for each shooting time period as a preprocessing step for deriving satisfaction for each shooting time period. Then, it converts the obtained image-related evaluation values ​​into satisfaction using a satisfaction conversion table. The satisfaction-related information 156 may consist only of specific attributes, or of specific attributes and setting attributes, or it may be information that associates satisfaction with the attributes of the user 14, similar to the satisfaction-related information 151 in the 4_1 embodiment described above.

[0108] Figure 27 shows an example of deriving satisfaction levels for four shooting time slots: 09:00-11:59, 12:00-14:59, 15:00-17:59, and 18:00-20:59. Figure 27 also shows an example of generating satisfaction-related information 156A for 09:00-11:59, 156B for 12:00-14:59, 156C for 15:00-17:59, and 156D for 18:00-20:59.

[0109] Thus, in the 4th-2nd embodiment, satisfaction levels are derived for each time slot in which images 24 are taken at the target event. This allows for the generation of satisfaction-related information 156 for each time slot. The organizer 15 can use this satisfaction-related information 156 to find out what kind of user 14 has high satisfaction levels for each time slot. For example, if the target event was a music festival where users (event attendees) were allowed to take photos of multiple artists, the organizer can find out which time slots (which artists) are popular with which types of users 14.

[0110] Embodiments 4_1 and 4_2 may be combined and implemented. Specifically, satisfaction levels may be derived for each shooting location and time period of the image 24 in the target event.

[0111] The attributes of user 14 and a table 66 containing satisfaction levels for each user ID may be distributed to the organizer terminal 12. In this case, the browser control unit 80 of the organizer terminal 12 may output an information display screen to the display 44B, for example, for male users 14, which includes a histogram with the number of users on the vertical axis and satisfaction levels on the horizontal axis.

[0112] As an example, as shown in Figure 28, the information processing server 10 may generate user movement path information 160 for each movement path to each location of the target event, accumulating the number of users 14 who actually followed each movement path, and distribute the generated user movement path information 160 to the organizer terminal 12. Which movement path a user 14 followed can be determined from the location and date and time of the image 24. Figure 28 shows an example in which the number of users 14 is aggregated for each of the six possible movement paths that go through the three locations A, B, and C of the target event, such as A→B→C, B→A→C, and C→A→B.

[0113] According to the user movement path information 160, the organizer 15 can find out which movement paths are being followed and by how many users 14. Therefore, the organizer 15 can operate the event in a way that is tailored to the movement paths of the users 14, such as by setting up restaurants or souvenir shops along movement paths that are being followed by many users 14, or by setting up new attractions along movement paths that are not being followed by many users 14 to distribute the flow of users 14.

[0114] As an example, as shown in Figure 29, the information processing server 10 may generate user gathering and dispersal information 162 for each location and time period in which an image 24 was taken at the target event, and distribute the generated user gathering and dispersal information 162 to the organizer terminal 12.

[0115] According to the user gathering and dispersal information 162, the organizer 15 can find out how many users 14 are gathered at each location and at what time. Therefore, the organizer 15 can adjust operations at each location according to the gathering and dispersal of users 14, such as increasing the number of security guards during times when many users 14 are gathered, or setting up food trucks to sell snacks during times when many users 14 are gathered.

[0116] As an example, as shown in Figure 30, the information processing server 10 may analyze the subjects of images 24 stored in the image DB 25, for example, images 24 taken in the most recent month, and distribute the subject with the highest increase in the number of times it appears in the image 24 compared to one month ago as trend information 170 to the organizer terminal 12. In Figure 30, an example is shown where the subject with the highest increase in the number of times it appears in the image 24 compared to one month ago is fried chicken.

[0117] According to Trend Information 170, Organizer 15 can find out what is currently trending. Therefore, Organizer 15 can operate the event in a way that aligns with current trends, such as selling products related to Trend Information 170.

[0118] Furthermore, the images 24 used as the basis for deriving the trend information 170 may be limited to images 24 taken by users 14 with specific attributes, such as women in their 20s. Alternatively, the images 24 may be limited to images 24 taken by users 14 with specified attributes.

[0119] Satisfaction-related information has little value unless a sufficient number of users 14 who participated in the target event have been gathered. Therefore, it is preferable to refrain from distributing satisfaction-related information until the number of users 14 who participated in the target event exceeds a predetermined threshold.

[0120] The method of presenting satisfaction-related information to the event organizer 15 is not limited to the example of distributing satisfaction-related information to the organizer's terminal 12. The satisfaction-related information may also be printed out on paper and mailed to the event organizer 15, or attached to an email and sent to the event organizer 15.

[0121] The user 14 attributes may include hobbies, preferences, and personality traits. Image-related evaluation values, such as the number of photos taken, may be used directly as satisfaction levels. The operators of the information processing server 10 and the image database server 21 may be the same as, or different from, the operators of the event information database server 20.

[0122] The method of applying for an event is not limited to the example method in which user 14 searches for and applies for the event information 22 of the event they desire. Alternatively, the information processing server 10 may distribute recommended event information 22 based on the configured attributes to the user terminal 11, and user 14 may apply for the event in the recommended event information 22.

[0123] The information processing server 10 may handle some of the functions of the browser control unit 80 of the organizer terminal 12. Specifically, the information processing server 10 generates various screens such as the information display screen 85 and outputs them to the organizer terminal 12 in the form of web-distributed screen data created using a markup language such as XML (Extensible Markup Language). In this case, the browser control unit 80 of the organizer terminal 12 reproduces the various screens to be displayed on the web browser based on the screen data and displays them on the display 44B. Note that other data description languages ​​such as JSON (Javascript® Object Notation) may be used instead of XML.

[0124] The user terminal 11 that sends the image 24 to the information processing server 10 and the user terminal 11 that receives the event information 22 from the information processing server 10 may be different. For example, if there are multiple user terminals 11 with the same user 14 account, the image 24 may be sent from one of them to the information processing server 10, and the event information 22 may be distributed from the information processing server 10 to another of them.

[0125] The hardware configuration of the computers constituting the information processing server 10 can be modified in various ways. For example, the information processing server 10 can be composed of multiple computers separated as hardware, in order to improve processing power and reliability. For example, the functions of the request receiving unit 55 and the acquisition unit 56, and the functions of the output unit 57 and the distribution control unit 58 can be distributed among two computers. In this case, the information processing server 10 is composed of two computers. Alternatively, the information processing server 10, the event information DB server 20, and the image DB server 21 may be integrated into a single server.

[0126] Thus, the hardware configuration of the computer in the information processing server 10 can be appropriately changed according to the required performance, such as processing power, security, and reliability. Furthermore, not only the hardware, but also the application programs such as the operating program 50 and the marketing AP 75 can, of course, be duplicated or distributed and stored on multiple storage devices for the purpose of ensuring security and reliability.

[0127] In each of the above embodiments, the hardware structure of the Processing Unit, which executes various processes such as the request receiving unit 55, acquisition unit 56, output unit 57, distribution control unit 58, browser control unit 80, and analysis unit 140, can be the following types of processors. These types of processors include CPUs 42A and 42B, which are general-purpose processors that execute software (operation program 50 and marketing AP 75) and function as various processing units, as well as programmable logic devices (PLDs) such as FPGAs (Field Programmable Gate Arrays) whose circuit configuration can be changed after manufacturing, and / or dedicated electrical circuits such as ASICs (Application Specific Integrated Circuits) which have a circuit configuration specifically designed to execute a particular process.

[0128] A single processing unit may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, and / or a combination of a CPU and an FPGA). Alternatively, multiple processing units may be composed of a single processor.

[0129] Examples of configuring multiple processing units with a single processor include, firstly, a configuration where one or more CPUs and software combine to form a single processor, which then functions as multiple processing units, as exemplified by client and server computers. Secondly, a configuration using a processor that realizes the functions of the entire system, including multiple processing units, on a single IC (Integrated Circuit) chip, as exemplified by System-on-a-Chip (SoC). Thus, various processing units are configured, in terms of hardware structure, using one or more of the above-mentioned processors.

[0130] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits (Circuitry) that combine circuit elements such as semiconductor elements.

[0131] The technology of this disclosure can be appropriately combined with the various embodiments and / or variations described above. Furthermore, it is understood that various configurations can be adopted without departing from the spirit of the invention, and the invention is not limited to the embodiments described above. Moreover, the technology of this disclosure extends not only to programs but also to storage media for storing programs non-temporarily.

[0132] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0133] In this specification, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0134] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. [Explanation of symbols]

[0135] 2. Information Processing Systems 10. Information Processing Server 11 User terminals 12 Organizer's terminal 13 Networks 14 users 15 Organizers 20. Event Information Database Server (Event Information DB Server) 21. Image Database Server (Image DB Server) 22 Event Information 23 Event Information Database (Event Information DB) 24 images 25 Image Database (Image DB) Satisfaction-related information for items 26, 107, 135, 151, 151A-151C, 156, 156A-156D 30 categories 32 Basic information 33. Applicant User Information 35 Image folders 36. Additional Information 37 Attribute information 40, 40A, 40B storage 41 memory 42, 42A, 42B CPUs 43 Communications Department 44, 44B displays 45, 45B Input Devices 46 Bus Line 50 Operating Programs 51, 90, 95 Satisfaction Conversion Table 55 Request Reception Department 56 Acquisition Department 57 Derivation part 58 Distribution Control Unit 60. Request for information distribution related to customer satisfaction. 61 Acquisition request 65, 66, 68A~68D, 91, 92, 96, 97, 101, 120, 121, 150, 155 Table 75 Marketing Application Program (Marketing AP) 80 Browser Control Unit 85, 110, 130 information display screen 86 Specific attributes 87, 112, 131 Confirmation button 100 Weighting Coefficient Table 105 Setting Attribute Table 111 Configuration attributes 122 Notification Conditions 123 Recommended Changes Notification 140 Analysis Department 141 Facial expression analysis results 145 Satisfaction Level Adjustment Criteria 160 User movement path information 162 User gathering and dispersal information 170 Trend information ST100, ST110, ST120, ST130, ST140, ST1301, ST1302, ST1303, ST1304, ST1305 Step

Claims

1. Processor and The processor comprises, The aforementioned processor, We acquire images taken by the user during the target event to measure user satisfaction. Based on the conditions relating to image-related evaluation values, which are at least one of the following: the number of images taken, the number of times the images have been viewed, and the number of times the images have been posted, the user's satisfaction with the target event is derived. The user's attributes and satisfaction-related information regarding the satisfaction level are presented to the organizer of the target event. Information processing device.

2. The aforementioned processor, By statistically analyzing the satisfaction level, specific attributes are derived that represent users who tend to like the target event among the users who participated in the target event. The information processing device according to claim 1, which presents the specified attribute as satisfaction-related information.

3. The aforementioned processor, The information processing apparatus according to claim 2, wherein the higher the user's satisfaction level, the heavier the weight given to the attributes when deriving the specific attribute.

4. The aforementioned processor, The information processing device according to claim 2 or 3, which, in addition to the specified attributes, presents setting attributes, which are user attributes set by the organizer for the target event, as satisfaction-related information.

5. The aforementioned processor, A first representative satisfaction level is derived that represents the satisfaction level of all users who participated in the aforementioned event, and a second representative satisfaction level is derived that represents the satisfaction level of users who participated in the aforementioned event and whose specified attributes were set by the organizer for the aforementioned event. The information processing device according to any one of claims 1 to 4, wherein if the second representative satisfaction level is lower than the first representative satisfaction level, and the absolute value of the difference between the first representative satisfaction level and the second representative satisfaction level satisfies a preset threshold condition, a notification prompting the organizer to change the setting attribute is presented to the organizer.

6. The aforementioned processor, An information processing device according to any one of claims 1 to 5, which presents information relating the satisfaction level to the user's attributes as satisfaction-related information.

7. The aforementioned processor, Furthermore, the information processing apparatus according to any one of claims 1 to 6, which derives the satisfaction level based on the results of analyzing the facial expressions of the person in the image.

8. The aforementioned processor, An information processing device according to any one of claims 1 to 7, which derives the satisfaction level for at least one of the shooting location and shooting time of the image in the target event.

9. To obtain images taken by the user during the target event for measuring user satisfaction, Based on the conditions relating to image-related evaluation values, which include at least one of the following: the number of images taken, the number of times the images have been viewed, and the number of times the images have been posted, the user's satisfaction with the target event is derived, and To provide the organizer of the target event with the user's attributes and satisfaction-related information regarding the satisfaction level. A method for operating an information processing device, including the device itself.

10. To obtain images taken by the user during the target event for measuring user satisfaction, Based on the conditions relating to image-related evaluation values, which include at least one of the following: the number of images taken, the number of times the images have been viewed, and the number of times the images have been posted, the user's satisfaction with the target event is derived, and To provide the organizer of the target event with the user's attributes and satisfaction-related information regarding the satisfaction level. An operating program for an information processing device that causes a computer to perform a process that includes [specific details].

Images