Information processing system, information processing method, and non-transitory computer-readable medium

Abstract

An information processing device (10) is provided with a control unit (11). A control unit (11) acquires a plurality of first logs including at least an IP address, a date, and a time from a first user terminal (20) to which a unique ID has been set, retrieves group information from a first DB (161) in which the unique ID and group information are stored in association with each other, using the unique ID of the first user terminal (20) as a keyword, and transmits the retrieved group information to the first user terminal (20). When there is a change in the IP address within a predetermined period in the plurality of acquired first logs, the IP address within the target period is estimated on the basis of the regularity of the change in the IP address, and information in which at least the estimated IP address is associated with the searched group information is stored in the second database.

Description

Technical Field

[0001] The present invention relates to an information processing system, an information processing method, and a non-transitory computer-readable medium. Background Art

[0002] It is known that a user's group is identified based on their IP (Internet Protocol) address, and this group information is used when distributing advertisements. For example, Patent Document 1 describes an advertisement distribution device that stores a correspondence between IP addresses and group IDs and determines the group ID based on the IP address of the PC terminal to which the advertisement is distributed.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Laid-Open No. 2011-191614 Summary of the Invention

[0006] Problems to be solved by the invention

[0007] The correspondence between global IP addresses and groups is known only by the ISP (Internet Service Provider) that the group has signed up with, making it difficult to accurately determine from the outside. This is especially true for IP addresses that fluctuate, making it difficult to accurately determine their correspondence with groups.

[0008] In view of the above problems, an object of the present invention is to provide an information processing system, an information processing method, and a non-transitory computer-readable medium that can easily determine the correspondence between a global IP address and a community.

[0009] Means for solving problems

[0010] An information processing system according to one embodiment of the present invention has one or more processors, a memory, and one or more programs. The one or more programs are stored in the memory and are configured to be executed by the one or more processors. The one or more programs include instructions for executing the following: obtaining a plurality of first logs containing at least an IP address, a date, and a time from a first user terminal with a unique ID set; using the unique ID of the first user terminal as a keyword, retrieving group information from a first database storing the unique ID in association with group information; when there is a change in the IP address within a specified period in the plurality of first logs obtained, inferring the IP address within the target period based on the regularity of the change in the IP address; and storing in a second database information that corresponds at least the inferred IP address to the retrieved group information.

[0011] An information processing method according to one embodiment of the present invention is executed on a computer. The method comprises: acquiring a plurality of first logs containing at least an IP address, date, and time from a first user terminal having a unique ID; using the unique ID of the first user terminal as a key, retrieving group information from a first database that stores unique IDs in association with group information; when IP addresses fluctuate within a predetermined period in the plurality of acquired first logs, inferring IP addresses within a target period based on the regularity of the IP address fluctuations; and storing in a second database information that associates at least the inferred IP addresses with the retrieved group information.

[0012] A non-transitory computer-readable medium according to one embodiment of the present invention stores one or more programs. The one or more programs include instructions that, when executed by a computer, cause the computer to: obtain a plurality of first logs containing at least an IP address, date, and time from a first user terminal with a unique ID; retrieve group information from a first database that stores unique IDs in association with group information, using the unique ID of the first user terminal as a key; when IP addresses fluctuate within a specified period in the plurality of acquired first logs, infer IP addresses within a target period based on the regularity of the IP address fluctuations; and store in a second database information that associates at least the inferred IP addresses with the retrieved group information.

[0013] Effects of the Invention

[0014] According to the present invention, it is possible to provide an information processing system, an information processing method, and a non-transitory computer-readable medium capable of easily determining the correspondence between a global IP address and a community. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a block diagram showing the configuration of the system according to the first embodiment.

[0016] Figure 2 This is a flowchart showing the flow of information processing by the information processing device according to the first embodiment.

[0017] Figure 3 This is a block diagram showing a schematic configuration of a system according to the second embodiment.

[0018] Figure 4 This is a block diagram showing the hardware configuration of a first user terminal according to Embodiment 2.

[0019] Figure 5 This is a diagram showing an example of the appearance of a first user terminal according to Embodiment 2.

[0020] Figure 6 This is a block diagram showing the hardware configuration of a second user terminal according to the second embodiment.

[0021] Figure 7 This is a block diagram showing the hardware configuration of an information processing device according to the second embodiment.

[0022] Figure 8 This is a diagram showing an example of the configuration of a storage unit according to the second embodiment.

[0023] Figure 9 This is a diagram showing an example of the data structure of the determination table according to the second embodiment.

[0024] Figure 10 This is a diagram showing an example of the data structure of the estimation table according to the second embodiment.

[0025] Figure 11 This is a diagram showing an example of the functional configuration of a control unit according to the second embodiment.

[0026] Figure 12 This is a flowchart showing the flow of registration processing by the control unit in the second embodiment.

[0027] Figure 13 This is a flowchart showing the flow of the second saving process by the control unit according to the second embodiment.

[0028] Figure 14 This is a diagram showing the concept of the second storage process in the second embodiment.

[0029] Figure 15 This is a flowchart showing the flow of the third saving process by the control unit in the second embodiment.

[0030] Figure 16 This is a diagram showing the concept of the third storage process in the second embodiment.

[0031] Figure 17 This is a flowchart showing the flow of the first saving process by the control unit according to the second embodiment.

[0032] Figure 18 This is a diagram showing the concept of the first storage process in the second embodiment.

[0033] Figure 19 This is a flowchart showing the flow of generation processing by the control unit in the second embodiment.

[0034] Figure 20 This is a diagram showing a first example of the data structure of analytical data according to the second embodiment.

[0035] Figure 21This is a diagram showing a first example of the data structure of the analysis results according to the second embodiment.

[0036] Figure 22 This is a diagram showing a second example of the data structure of analytical data according to the second embodiment.

[0037] Figure 23 This is a diagram showing a second example of the data structure of the analysis results according to the second embodiment.

[0038] Figure 24 This is a block diagram showing a schematic configuration of a system according to a third embodiment.

[0039] Figure 25 This is a diagram showing an example of the functional configuration of a control unit according to the third embodiment.

[0040] Figure 26 This is a flowchart showing the flow of comparison processing by the control unit in the third embodiment.

[0041] Figure 27 This is a diagram showing an example of the data structure of measurement data according to the third embodiment. DETAILED DESCRIPTION

[0042] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the drawings, the same or corresponding elements are denoted by the same reference numerals, and for clarity of description, repeated descriptions will be omitted as necessary.

[0043] <Implementation Method 1>

[0044] First, Embodiment 1 of the present disclosure will be described. Figure 1 1 is a block diagram showing the configuration of a system 1 according to Embodiment 1. The system 1 is a computer system including an information processing device 10 and a first user terminal 20. The information processing device 10 and the first user terminal 20 are communicably connected via a network NW such as the Internet.

[0045] The first user terminal 20 is a terminal belonging to a predefined group and has a predefined unique ID corresponding to the group. The first user terminal 20 belonging to the group means that the first user terminal 20 is located at the group's location, such as a group event venue. Examples of the first user terminal 20 include image forming devices such as multifunction devices, personal computers, tablet computers, smartphones, wireless LAN routers, and smart speakers.

[0046] A group is a collection of people who share a purpose or space, etc. Examples of groups include companies, departments, clubs, families, facility users, and apartment residents.

[0047] Information processing device 10 is a computer that determines the correspondence between groups and IP addresses. For example, information processing device 10 is a server. The IP address is a global IP address. Information processing device 10 includes a control unit 11, a communication unit 15, and a storage unit 16.

[0048] The control unit 11 includes a processor that controls the entire system of the information processing device 10. The control unit 11 implements the functions of the first acquisition unit 111, the search unit 112, the estimation unit 113, and the registration unit 114 by executing a program.

[0049] The first acquisition unit 111 receives and acquires a measurement log from a first user terminal 20, whose unique ID is known, via the communication unit 15. The measurement log is also referred to as a first log. The measurement log includes at least the IP address of the first user terminal 20 and the date and time. The IP address included in the measurement log is the IP address assigned when the first user terminal 20 connects to the network NW. The date and time included in the measurement log is the date and time the first user terminal 20 connects to the network NW, but it could also be the date and time the information processing device 10 receives the measurement log, or the date and time the first user terminal 20 transmits the measurement log. The measurement log may include the unique ID of the first user terminal 20. The first acquisition unit 111 receives the measurement log from the first user terminal 20 at predetermined time intervals. However, the first acquisition unit 111 may alternatively receive the measurement log from the first user terminal 20 in response to the occurrence of a predetermined event. In this way, the first acquisition unit 111 acquires multiple measurement logs with different dates and times by receiving measurement logs from the first user terminal 20 periodically or irregularly.

[0050] The search unit 112 uses the unique ID of the first user terminal 20, which is the source of the measurement log, as a key to search the first DB 161 for group information. The group information is not particularly limited, as long as it can identify the group where the first user terminal 20 is installed. It can include a group name, a corporate number, or other publicly available data related to the group.

[0051] The inference unit 113 determines whether any IP address changes within a specified period in the multiple measurement logs acquired by the first acquisition unit 111. For example, the specified period is a month, a week, a day, or an hour. If there are IP address changes within the specified period, the inference unit 113 infers the regularity of the IP address changes. The inference unit 113 then infers the IP address for the target period based on the inferred regularity of the IP address changes. The target period can be a future period or a past period.

[0052] The registration unit 114 stores, in the second DB 162 , at least information in which the group information retrieved by the search unit 112 and the IP address estimated by the estimation unit 113 are associated with each other.

[0053] The communication unit 15 is a communication interface for connecting to the network NW.

[0054] The storage unit 16 is a storage device having a non-transitory computer-readable medium or a physical storage medium. The storage unit 16 includes a first DB 161 and a second DB 162 .

[0055] The first DB 161 is a storage device that stores the correspondence between unique IDs and community information. The second DB 162 is a storage device that stores the correspondence between community information and IP addresses.

[0056] The first DB 161 and the second DB 162 are included in the storage unit 16 of the information processing device 10 , but may be included in an external device accessible by the information processing device 10 .

[0057] Figure 2 This is a flowchart illustrating the flow of information processing by the information processing device 10 according to Embodiment 1. First, the first acquisition unit 111 acquires multiple measurement logs containing IP addresses, dates, and times from a first user terminal 20 whose unique ID is known (S10: first acquisition step). Next, the search unit 112 accesses the first DB 161 and searches for group information using the unique ID of the first user terminal 20, which sent the measurement logs, as a key (S11: search step). Next, the inference unit 113 determines whether any IP address changes within a predetermined period in the multiple acquired measurement logs (S12). If there is an IP address change within the predetermined period ("Yes" in S12), the inference unit 113 infers the IP address during the target period based on the regularity of the IP address changes (S13: inference step). Next, the registration unit 114 registers information that associates at least the group information retrieved in S11 with the IP address inferred in S13 in the second DB 162 (S14: first storage step).

[0058] [Effect]

[0059] In this way, the information processing device 10 estimates the group IP address based on the regularity of IP address changes. Although it is particularly difficult to determine the group IP address when the IP address changes, the first embodiment can easily determine the correspondence between the group and the global IP address.

[0060] <Implementation Method 2>

[0061] Next, Embodiment 2 of the present disclosure will be described. Embodiment 2 is a specific example of Embodiment 1. Figure 3 This is a block diagram showing a schematic configuration of a system 1 according to a second embodiment.

[0062] The system 1 includes an information processing device 10, first user terminals 20-A and 20-B, second user terminals 30-A and 30-B, a log collection server 40, and an advertiser-side device 50. These are connected to a network NW and can communicate with each other.

[0063] Similar to the information processing device 10 in Embodiment 1, the information processing device 10 in Embodiment 2 determines the correspondence between groups and IP addresses based on the measurement logs acquired from the first user terminals 20-A and 20-B. Furthermore, the information processing device 10 in Embodiment 2 analyzes access by group based on the site logs of second user terminals 30-A and 30-B accessing the advertiser's website and the aforementioned correspondence. The information processing device 10 then provides the analysis results to the advertiser-side device 50.

[0064] First user terminals 20-A and 20-B are specific examples of first user terminals 20 in Embodiment 1. First user terminals 20-A and 20-B are multi-function devices with signage installed at locations of different groups A and B, respectively. First user terminals 20-A and 20-B are configured with unique IDs corresponding to the groups. First user terminals 20-A and 20-B have the function of posting advertisements. For example, first user terminals 20-A and 20-B obtain advertising data for their own groups from information processing device 10 or advertiser-side device 50 and display the advertising data. Furthermore, first user terminals 20-A and 20-B each periodically or irregularly transmit measurement logs to information processing device 10.

[0065] Second user terminals 30-A and 30-B are used by users (members) belonging to different groups A and B, respectively. Members may be employees, sales personnel, members, or other members of the group. Examples of second user terminals 30-A and 30-B include personal computers, smartphones, and tablets. Second user terminals 30-A and 30-B do not have unique IDs. Second user terminals 30-A and 30-B may or may not be portable.

[0066] Hereinafter, unless a group is specified, the first user terminals 20-A and 20-B are simply referred to as first user terminals 20. Furthermore, unless a group is specified, the second user terminals 30-A and 30-B are simply referred to as second user terminals 30.

[0067] The log collection server 40 obtains the site log when the second user terminal 30 accesses the advertiser's website and saves it in the site log DB 401. The log collection server 40 then sends the site log to the information processing device 10. The site log is also called the second log. The site log contains at least the IP address when the second user terminal 30 accesses the website, the date and time of the access, an identifier that directly or indirectly shows the user accessing the website, and log information related to web page browsing. For example, the above identifier is a user ID, a terminal ID, or a session ID (session ID). The user ID is an identifier inherent to the user accessing the website. The terminal ID is information that identifies the terminal accessing the website. The session ID is information that uniquely identifies the session of the user accessing the website. The site log may include a device fingerprint, which includes inherent information held by the hardware or software of the second user terminal 30 or the browser. For example, the site log is automatically sent to the log collection server 40 through a tag embedded in the advertiser's website visited by the second user terminal 30.

[0068] The advertiser-side device 50 is a computer used by the advertiser.

[0069] Figure 4 This is a block diagram showing the hardware configuration of the first user terminal 20 according to Embodiment 2. The first user terminal 20 includes a control unit 21 for controlling the entire system. The control unit 21 is connected to a communication unit 25, a storage unit 26, an input unit 27, a display unit 28, and an output unit 29 via a communication bus.

[0070] The control unit 21 includes a processor 22, ROM 23, and RAM 24. The processor 22 performs various information processing and control operations according to programs stored in the ROM 23 or the storage unit 26. The ROM 23 is a non-transitory storage medium such as a ROM (Read-only Memory) and stores various programs and data used by the processor 22 to perform various controls and calculations. The RAM 24 is a volatile storage medium such as a RAM (Random Access Memory) and is a storage area for temporarily storing information while the processor 22 is operating. Within the RAM 24, an area for performing various processes in this embodiment can be secured.

[0071] The communication unit 25 is a communication interface for connecting to the network NW. The storage unit 26 is a storage device including a non-transitory computer-readable medium or a physical storage medium.

[0072] The input unit 27 is an input device such as a keyboard, mouse, or touch panel that receives input from the user. The display unit 28 is a display device such as a CRT, liquid crystal display, organic EL display, or plasma display. The output unit 29 is an output device that prints the results of information processing performed by the control unit 21.

[0073] Figure 5 This figure shows an example of the appearance of a first user terminal 20 according to Embodiment 2. The control unit 21, communication unit 25, storage unit 26, input unit 27, and output unit 29 may constitute a conventional multifunction peripheral (MFP). Furthermore, as shown in this figure, the display unit 28 may be an external digital signage.

[0074] Figure 6 This is a block diagram showing the hardware configuration of the second user terminal 30 according to Embodiment 2. The second user terminal 30 includes a control unit 31 for controlling the entire system. The control unit 31 is connected to a communication unit 35, a storage unit 36, an input unit 37, and a display unit 38 via a communication bus.

[0075] The control unit 31 includes a processor 32, a ROM 33, and a RAM 34. The processor 32 performs various information processing and control operations according to programs stored in the ROM 33 or the storage unit 36. The ROM 33 is a non-transitory storage medium such as a ROM, and stores various programs and data used by the processor 32 to perform various controls and calculations. The RAM 34 is a volatile storage medium such as a RAM, and is a storage area for temporarily storing information while the processor 32 is operating. Within the RAM 34, an area for performing various processes in this embodiment can be secured.

[0076] The communication unit 35 is a communication interface for connecting to the network NW. The storage unit 36 is a storage device including a non-transitory computer-readable medium or a physical storage medium.

[0077] The input unit 37 is an input device such as a keyboard, a mouse, or a touch panel for receiving input from a user. The display unit 38 is a display device such as a CRT, a liquid crystal display, an organic EL display, or a plasma display.

[0078] Figure 7 1 is a block diagram showing the hardware configuration of the information processing device 10 according to Embodiment 2. The information processing device 10 includes an input unit 17 and a display unit 18 in addition to a control unit 11 , a communication unit 15 , and a storage unit 16 .

[0079] The control unit 11 includes a processor 12, a ROM 13, and a RAM 14. The processor 12 performs various information processing and control operations according to programs stored in the ROM 13 or the storage unit 16. The ROM 13 is a non-transitory storage medium such as a ROM, and stores various programs and data used by the processor 12 to perform various controls and calculations. The RAM 14 is a volatile storage medium such as a RAM, and is a storage area for temporarily storing information while the processor 12 is operating. Within the RAM 14, an area for performing various processes in this embodiment can be secured.

[0080] The input unit 17 is an input device such as a keyboard, mouse, or touch panel that receives input from the user. The display unit 18 is a display device such as a CRT, liquid crystal display, organic EL display, or plasma display. The input unit 17 and the display unit 18 are not essential.

[0081] Figure 8 1 is a diagram showing an example of the configuration of the storage unit 16 according to Embodiment 2. The storage unit 16 includes a measurement log DB 160 and a third DB 163 in addition to the first DB 161 and the second DB 162 .

[0082] The measurement log DB 160 is a storage device that stores the measurement log received from the first user terminal 20. The measurement log includes an IP address, a unique ID, and a date and time.

[0083] The third DB 163 is a storage device that stores group information, analytical data to be subjected to access analysis, and analysis results of the information processing device 10 in association with each other.

[0084] In addition, the first DB 161 is generated in advance based on known information.

[0085] Here, in the second embodiment, the second DB 162 includes a determination table 1620 and an inference table 1621 .

[0086] Figure 9 This is a diagram showing an example of the data structure of the identification table 1620 according to Embodiment 2. The identification table 1620 associates a record number, a community name as an example of community information, a fixed IP flag, a target period, and a global IP address.

[0087] The record number indicates the order in which the record is registered in the determination table 1620 .

[0088] The fixed IP flag is a variable that indicates whether the global IP address is a fixed IP address. For example, if the fixed IP flag is "ON", the global IP address is a fixed IP address. If the fixed IP flag is "OFF", the global IP address is a variable IP address.

[0089] The identification table 1620 is generated by a registration process described later by the information processing device 10. However, the identification table 1620 may also include a record related to a group with a known IP address in advance.

[0090] Figure 10 This is a diagram showing an example of the data structure of the estimation table 1621 according to Embodiment 2. The estimation table 1621 associates a record number, a community name as an example of community information, a regularity flag, a target period, and an estimated global IP address.

[0091] The record number indicates the order in which the record is registered in the inference table 1621 .

[0092] The regularity flag is a variable indicating whether the change of the global IP address during the measurement period has regularity.

[0093] An inferred global IP address is a global IP address that is inferred to be a group IP address during the target period. An inferred global IP address can be a single IP address or include multiple IP addresses.

[0094] Note that the estimation table 1621 is generated by a registration process of the information processing device 10 described later.

[0095] Figure 11 This diagram shows an example of the functional configuration of the control unit 11 according to Embodiment 2. The control unit 11 includes a first acquisition unit 111 , a search unit 112 , an estimation unit 113 , and a registration unit 114 , as well as a second acquisition unit 115 , a generation unit 116 , and an analysis unit 117 .

[0096] The first acquisition unit 111 and the search unit 112 are the same as those in the first embodiment, and therefore their description is omitted.

[0097] Similar to the first embodiment, the inference unit 113 determines whether there is any change in the IP address within the predetermined measurement period in the multiple measurement logs acquired by the first acquisition unit 111. If there is any change in the IP address during the measurement period, the inference unit 113 determines whether the change in the IP address corresponding to the unique ID is regular. If the change in the IP address is regular, the inference unit 113 and the registration unit 114 jointly perform the first storage process described below. As a result, the control unit 11 stores information that associates at least the inferred IP address with the retrieved group information in the inference table 1621 of the second database 162.

[0098] If the IP address has not changed during the measurement period, the estimation unit 113 executes the second storage process described below together with the registration unit 114. As a result, the control unit 11 stores information that associates at least the unchanged IP address with the retrieved group information as a single record in the identification table 1620 of the second DB 162.

[0099] On the other hand, if there is a change in the IP address during the measurement period, the estimation unit 113 executes the third storage process described below together with the registration unit 114. Thus, the control unit 11 stores information that associates at least the IP address included in the measurement log in which the IP address has changed with the retrieved group information as a single record in the identification table 1620 of the second DB 162.

[0100] The second acquisition unit 115 acquires the site log when the second user terminal 30 accesses a predetermined website from the log collection server 40. The predetermined website is, for example, an advertiser's website, but may be any website as long as it includes content related to the advertiser.

[0101] Generator 116 identifies the group information corresponding to the IP address and the access date and time contained in the site log from second DB 162. Generator 116 generates, as analysis data, information that associates at least the log information related to web page browsing contained in the site log, the access date and time, and the identified group information. Generator 116 then stores the analysis data in third DB 163.

[0102] The analyzing unit 117 performs access analysis based on the analysis data and stores the analysis results in the third DB 163. The analyzing unit 117 then transmits the analysis results to the advertiser-side device 50 via the communication unit 15.

[0103] Figure 12 This is a flowchart showing the flow of registration processing by the control unit 11 according to the second embodiment.

[0104] First, the first acquisition unit 111 collects measurement logs containing unique IDs, IP addresses, and date and time from the first user terminals 20-A and 20-B, each of which has a known unique ID (S20: first acquisition step). Next, the control unit 11 repeats the processes shown in S21 to S26 for each unique ID of the first user terminal 20 that has been sent as the source. In S21, the search unit 112 accesses the first DB 161 and searches for group information using the unique ID as a keyword (S21: search step). Next, the inference unit 113 determines whether there is a change in the IP address during the measurement period in the multiple measurement logs obtained (S22). The fact that there is no change in the IP address during the measurement period includes not only the case where the IP address does not change at all during the measurement period, but also the case where the change in the IP address during the measurement period is within a specified range. If the IP address has not changed during the measurement period ("No" in S22), that is, if the IP address is a fixed IP address, the estimation unit 113 and the registration unit 114 perform a second storage process (S23: second storage step). If there is an unprocessed unique ID, the control unit 11 returns the process to S21.

[0105] On the other hand, when the IP address changes during the measurement period (YES in S22 ), that is, when the IP address is a changed IP address, the estimation unit 113 and the registration unit 114 execute a third storage process ( S24 : third storage step).

[0106] Next, the inference unit 113 determines whether the changes in the IP address are regular (S25). In this case, the inference unit 113 can determine whether the changes are regular based on at least one of the number of times the same IP address appears, the periodicity of the IP address's appearance, and the magnitude of the IP address's fluctuation. Furthermore, the inference unit 113 can also determine the Internet Service Provider (ISP) based on the IP addresses included in the measurement logs showing IP address fluctuations, and determine whether regularity is present based on the ISP. This allows the inference unit 113 to easily infer the regularity of IP address changes.

[0107] If it is determined that the IP address changes are regular ("Yes" in S25), the inference unit 113 and the registration unit 114 execute the first storage process (S26). If there are any unprocessed unique IDs, the control unit 11 returns the process to S21. On the other hand, if it is not determined that the IP address changes are regular ("No" in S25), if there are any unprocessed unique IDs, the process returns to S21.

[0108] Figure 13 This is a flowchart showing the flow of the second storage process by the control unit 11 according to the second embodiment. Figure 14 This is a diagram showing the concept of the second storage process in the second embodiment.

[0109] The inference unit 113 determines whether the IP address has changed during the measurement period. If not, it determines that the IP address is a fixed IP address (S230). As an example, the measurement period is set to November 1, 2022, to November 30, 2022. During this measurement period, the IP address of Co., Ltd. is fixed at 198.51.100.1, so the inference unit 113 sets the fixed IP flag to "on."

[0110] Then, the registration unit 114 sets the target period based on the measurement period (S231). Figure 14 In the example shown, the registration unit 114 sets the same period as the measurement period as the target period (November 1, 2022 to November 30, 2022). However, the present invention is not limited to this. For example, the registration unit 114 may set a one-month period several months after the measurement period as the target period.

[0111] Next, the registration unit 114 stores the associated fixed IP address, the retrieved group information, and the target period in a new record in the identification table 1620 of the second DB 162 (S232). Thus, the registration unit 114 can aggregate information from multiple measurement logs within the measurement period into a single record. This allows logs with dates and times without actual measurement results to be supplemented, while also reducing the amount of data stored in the identification table 1620.

[0112] Alternatively, the registering unit 114 may store information of a plurality of measurement logs during the measurement period together with the retrieved group information as a plurality of records in the identification table 1620. In this case, the data volume can be reduced by reducing the number of records to a smaller number than the number of basic measurement logs.

[0113] Figure 15 This is a flowchart showing the flow of the third saving process by the control unit 11 according to the second embodiment. Figure 16 This is a diagram showing the concept of the third storage process in the second embodiment.

[0114] The inference unit 113 determines whether the IP address has changed during the measurement period, and if so, determines that the IP address has changed (S240). Figure 16 As shown in , for example, the measurement period is set to November 1, 2022 to November 30, 2022. Figure 16 As shown in FIG. 1 , the IP address of RO Co., Ltd. has changed during the measurement period. Therefore, the inference unit 113 sets the fixed IP flag to "off".

[0115] Then, the estimation unit 113 detects the change timing within the measurement period (S241). Then, the estimation unit 113 sets the target period according to the change timing (S242). Figure 16 As shown, November 1, 2022, 12:00:00 and November 1, 2022, 12:00:01 are the change timings when the IP address is switched. The estimation unit 113 sets November 1, 2022, 12:00:00 to November 1, 2022, 12:00:59 and November 1, 2022, 12:01:00 to November 1, 2022, 17:59:59 as the target periods for each record.

[0116] The control unit 11 then repeats the processes shown in S243 and S244 for each record, that is, for each target period. In S243, the registering unit 114 selects a measurement log after a change from the measurement logs within the measurement period. The registering unit 114 can select the measurement log immediately after the change, but can also select any measurement log from immediately after the change until the next change.

[0117] Then, in S244, the registration unit 114 stores the information corresponding to the IP address included in the selected measurement log, the retrieved group information, and the target period as a new record in the identification table 1620 of the second DB 162. Therefore, the registration unit 114 omits creating records for IP addresses included in unselected measurement logs. This allows logs with dates and times without actual measurement results to be supplemented, while also reducing the amount of data stored in the identification table 1620.

[0118] Alternatively, the registering unit 114 may select multiple measurement logs after changes within the measurement period and store them together with the retrieved group information as multiple records in the identification table 1620. In this case, the data volume can be saved by making the number of records smaller than the number of selected measurement logs.

[0119] Figure 17 This is a flowchart showing the flow of the first saving process by the control unit 11 according to the second embodiment. Figure 18 This is a diagram showing the concept of the first storage process in the second embodiment.

[0120] First, the estimation unit 113 sets the target period based on the measurement period (S260). Figure 18 In the example shown, the estimation unit 113 sets the same period as the measurement period as the target period (November 1, 2022 to November 30, 2022). However, the present invention is not limited thereto. For example, the registration unit 114 may set a future month several months after the measurement period as the target period.

[0121] Next, the inference unit 113 infers the IP addresses during the target period based on the regularity of IP address changes determined in S25 (S261). For example, the inference unit 113 may infer the IP addresses based on at least one of the number of times the same IP address appears, the IP address appearance cycle, and the IP address fluctuation range. Alternatively, for example, the inference unit 113 may infer the IP addresses during the target period based on the regularity corresponding to the identified ISP. Alternatively, for example, the inference unit 113 may generate a regression equation between the IP addresses during the target period and the date and time to infer the IP addresses during the target period.

[0122] Then, the registration unit 114 stores information associating the IP address estimated in S261, the group information retrieved in S21, and the target period in the second DB 162 (S262). By implementing this method, the information processing device 10 can easily determine the correspondence between the group and the changed IP address.

[0123] Figure 19 This is a flowchart showing the flow of generation processing by the control unit 11 according to the second embodiment.

[0124] First, the second acquisition unit 115 collects site logs from the log collection server 40 when the second user terminal 30 accesses the website (S30: second acquisition step). Next, the generation unit 116 uses the IP address and access date and time contained in each site log as keywords to retrieve group information from the determination table 1620 or the inference table 1621 of the second database 162 (S31). For IP addresses that fluctuate and exhibit regularity, records exist in both the determination table 1620 and the inference table 1621. The generation unit 116 can determine whether to search the determination table 1620 or the inference table 1621 based on the required analysis accuracy.

[0125] Next, the generator 116 formats the site log data for each site log so that the site log data includes at least the access date and time, the group information retrieved in S31, and the session ID (S32). For example, the generator 116 may append the group information to the site log. Alternatively, in S32, the generator 116 may format the site log data so that the site log data includes a user ID or terminal ID in addition to or instead of the session ID.

[0126] Next, the control unit 11 repeats the processes shown in S33 to S37 for each group. In S33, the generation unit 116 collects the formatted data of the same group and generates analysis data including the collected formatted data (S33: generation step).

[0127] Next, the analysis unit 117 determines whether the amount of analytical data corresponding to one group is sufficient (S34). Here, the analysis unit 117 determines that the amount of analytical data is sufficient if the amount of formatted data included in the analytical data for one group (i.e., the number of site logs serving as the basis for the analytical data) is greater than a predetermined number. Alternatively, the analysis unit 117 may determine that the amount of analytical data is sufficient if the amount of formatted data included in the analytical data for a particular parameter of one group is greater than a predetermined number.

[0128] When it is determined that the amount of analytical data corresponding to one group is sufficient (YES in S34 ), the analyzer 117 analyzes the analytical data corresponding to the group ( S35 ).

[0129] On the other hand, if the amount of analytical data corresponding to a group is not determined to be sufficient ("No" in S34), the analysis unit 117 analyzes the analytical data using analytical data or analysis results of groups similar to the group (S36). The similarity of groups can be determined based on group attribute information, such as the group's industry type, customer base, whether it is profitable or deficit, market share, and organizational structure. For example, Groups A and B, which belong to the same automotive industry and have profitable attributes, are considered similar companies despite being different companies. Therefore, the analysis unit 117 uses Group A's data to supplement the missing data of Group B and conducts analysis.

[0130] Then, the analyzing unit 117 stores the analysis result in the third DB 163 ( S37 ). Alternatively, the analyzing unit 117 may transmit the analysis result to the advertiser-side device 50 .

[0131] Figure 20 This figure illustrates a first example of the data structure of analytical data in Implementation 2. For example, the log information contained in a site log includes reference source / medium, conversions, page URLs, and other metrics. Reference source / medium indicates the website or medium from which the user accessed the site, i.e., information indicating the reference source. In S32, the generator 116 generates formatted data by appending group information to the site log. Then, in S33, the generator 116 generates a collection of formatted data filtered by group name (Group A) as analytical data.

[0132] The analyzing unit 117 analyzes the analytical data for each group in S35. As an example, the analyzing unit 117 calculates a score for each reference source medium based on the conversion in the analytical data of group A.

[0133] Figure 21This figure shows a first example of the data structure of the analysis results of Implementation 2. The size of the score represents the conversion level of the medium. This figure shows that when advertising to employees of Group A, advertising via Medium A is most effective.

[0134] In this way, the analyzing unit 117 can identify effective media for advertising to the group by analyzing the analytical data.

[0135] Here, when the analysis data of group B does not contain enough data related to the conversion of medium c, the analysis unit 117 may substitute the score of medium c of group A, which is a similar enterprise, for the score of medium c of group B.

[0136] Figure 22 This figure shows a second example of the data structure of analytical data in Embodiment 2. In S33, the generator 116 further filters the set of formatted data, filtered by group name (Group A), using the session ID, and identifies the access path based on the evolution of the reference source medium. Generator 116 then collects access date and time, session ID, access path, and other log information for each group, generating the collected data as analytical data.

[0137] The analyzing unit 117 analyzes the analytical data for each group in S35. As an example, the analyzing unit 117 calculates a score for each access path based on the conversion in the analytical data of group A.

[0138] Figure 23 This figure shows a second example of the data structure of the analysis results of Implementation 2. The size of the score indicates the conversion level of the access path. This figure shows that when advertising to employees of Group A, directing the advertisement from Medium A to Medium B is the most effective.

[0139] [Effect]

[0140] According to the second embodiment, the same effects as those of the first embodiment are achieved.

[0141] Furthermore, if there is no change in the IP address during the measurement period in multiple measurement logs, the control unit 11 of the information processing device 10 stores at least the information associating the IP address with the community information as one record. This can reduce the amount of data stored in the identification table 1620.

[0142] Furthermore, if IP addresses change during the measurement period in multiple measurement logs, the control unit 11 of the information processing device 10 stores, for each change, information that associates at least the IP address and community information contained in the measurement log that changed as a single record. This reduces the amount of data stored in the identification table 1620.

[0143] According to the second embodiment, the correspondence between groups and global IP addresses can be easily determined, thereby facilitating group-based analysis of visits to advertiser websites. Furthermore, according to the second embodiment, the accuracy of the correspondence between groups and global IP addresses is improved, thereby improving the accuracy of group-based analysis of visits to advertiser websites.

[0144] The measurement log DB 160 , the first DB 161 , the second DB 162 , and the third DB 163 are included in the storage unit 16 of the information processing device 10 , but may be included in an external device accessible by the information processing device 10 .

[0145] <Implementation Method 3>

[0146] Next, a third embodiment of the present invention will be described. Figure 24 This is a block diagram showing the schematic configuration of system 1a according to Embodiment 3. System 1a has a fundamentally similar configuration to system 1. However, system 1a differs from system 1 in that it includes an information processing device 10a, a third user terminal 60-C, and a second user terminal 30-C instead of information processing device 10.

[0147] Group C is a different group from Group A, but similar to Group A. More specifically, Group C is a group whose similarity to Group A exceeds a predetermined threshold. Group similarity can be determined based on group attribute information, such as the group's industry, customer base, whether it is profitable or in deficit, market share, and organizational structure.

[0148] The third user terminal 60-C is an image forming device such as a multifunction device, a wireless LAN router, or a smart speaker installed in group C. The third user terminal 60-C is a terminal with a unique ID, but unlike the first user terminal 20, it does not have the function of posting advertisements. As an example, the third user terminal 60-C is a multifunction device without a sign.

[0149] The second user terminal 30 -C is also referred to as a fourth user terminal. The second user terminal 30 -C is a second user terminal 30 used by a user belonging to group C. The second user terminal 30 -C does not have a unique ID.

[0150] The information processing device 10 a differs from the information processing device 10 in that it includes a control unit 11 a instead of the control unit 11 .

[0151] Figure 25 1 is a diagram showing an example of the functional configuration of the control unit 11 a according to Embodiment 3. The control unit 11 a includes a third acquisition unit 118 and a comparison unit 119 in addition to the configuration of the control unit 11 .

[0152] The third acquisition unit 118 receives and acquires the posting log from the first user terminal 20 via the communication unit 15. The posting log is also called a third log. The posting log is a log related to the posting of advertisement data by the first user terminal 20 and contains information related to the posting date and time and the content of the posting.

[0153] When the content published in the publication log is associated with a specified group, the comparison unit 119 compares the publication date and time with the access date and time included in the site log. The specified group may be an advertiser. Furthermore, when the comparison result satisfies a specified condition, the comparison unit 119 determines that the publication effect has been achieved. For example, the specified condition may be that the publication date and time is before the access date and time. Furthermore, for example, in addition to the above conditions, the specified conditions may also include at least one of the following conditions: the period from the publication date and time to the access date and time is within a specified period; and the presence of a conversion. This makes it possible to easily measure the effectiveness of advertising based on the relationship between advertising and access.

[0154] Furthermore, the comparison unit 119 compares the log information from the site log when the second user terminal 30-A of group A accesses the advertiser's website with the log information from the site log when the second user terminal 30-C of group C accesses the advertiser's website. This makes it possible to easily measure the effectiveness of advertising based on whether or not an advertisement is posted. The site log when the second user terminal 30-C accesses the advertiser's website is also referred to as the fourth log. Furthermore, the step in which the second acquisition unit 115 acquires the fourth log is also referred to as the fourth acquisition step.

[0155] Then, the comparison unit 119 transmits various comparison results to the advertiser-side device 50. This allows feedback on the effectiveness of advertisement distribution to be given to the advertiser.

[0156] Figure 26 This is a flowchart illustrating the flow of comparison processing by the control unit 11a in Embodiment 3. First, the control unit 11a repeats the processes shown in S40 to S46 for each group. In S40, the third acquisition unit 118 collects site logs from the log collection server 40 when the second user terminal 30 accesses the advertiser's content.

[0157] Next, the comparison unit 119 determines whether the first user terminal 20, the destination for the advertisement, is located in the location of the group to which the second user terminal 30 belongs (S41). Specifically, the comparison unit 119 uses the second database 162 to identify the group based on the IP address and access date and time in the site log. The comparison unit 119 then searches the first database 161 using the group information as a key. If a corresponding unique ID is found, the comparison unit 119 determines that the first user terminal 20 is located.

[0158] If the first user terminal 20 is not installed at the group's location ("No" in S41), the comparison unit 119 advances the process to S46. On the other hand, if the comparison unit 119 determines that the first user terminal 20 is installed at the group's location ("Yes" in S41), the third acquisition unit 118 acquires the posting log from the first user terminal 20 (S42: third acquisition step).

[0159] Next, the comparison unit 119 determines whether the published content included in the advertisement data is related to the content on the advertiser's website (S43). Specifically, the comparison unit 119 makes this determination based on whether the degree of correlation between the attribute information of the published content and the attribute information of the content on the advertiser's website is greater than a predetermined value. If the published content is not related to the content on the advertiser's website ("No" in S43), the control unit 11a advances the process to S46.

[0160] On the other hand, if the posted content is related to the content of the advertiser's website ("YES" in S43), the comparison unit 119 determines whether the access date and time of the site log is after the posting date and time of the posted log (S44: determination step). If the access date and time is not after the posting date and time of the posted log ("NO" in S44), the control unit 11a advances the process to S46.

[0161] On the other hand, when the access date and time is after the posting date and time of the posting log (YES in S44 ), the comparison section 119 sets the flag with posting effect to ON ( S45 ).

[0162] Then, in S46 , the comparison unit 119 generates measurement data.

[0163] Figure 27 This diagram illustrates an example of the data structure of measurement data in Embodiment 3. Comparison unit 119 calculates the value of an indicator representing the effectiveness of the publication based on log information, dividing the data into pre-publication and post-publication data. Furthermore, comparison unit 119 includes the rate of change of the indicator before and after publication in the measurement data.

[0164] In S47, the comparison unit 119 compares the measurement data of similar companies based on whether or not the first user terminal 20 is installed (comparison step). For example, the comparison unit 119 compares the measurement data of group A, which has the first user terminal 20 installed, with the measurement data of group C, which does not have the first user terminal 20 installed. The comparison unit 119 then outputs the comparison result to the advertiser-side device 50 (output step).

[0165] [Effect]

[0166] According to the third embodiment, the same effects as those of the first and second embodiments are achieved.

[0167] Furthermore, if the content corresponding to the posting log is related to the content of the advertiser's website and is accessed after posting, the control unit 11a of the information processing device 10a determines that the posting is effective. This makes it possible to easily measure the effectiveness of advertising based on the relationship between advertising posting and access.

[0168] Furthermore, the control unit 11a of the information processing device 10a compares the log information based on whether or not an advertisement is posted. This makes it possible to easily measure the effectiveness of the advertisement posting based on whether or not an advertisement is posted.

[0169] <Other implementation methods>

[0170] While embodiments 1 to 3 illustrate the case where information processing devices 10 and 10a are single devices, some or all of the components of information processing devices 10 and 10a may be implemented using multiple information processing devices or circuits. In this case, the multiple information processing devices or circuits may be centrally located or distributed. For example, the information processing devices or circuits may be implemented by being connected to a client-server system, a cloud computing system, or the like via a communication network. Furthermore, the functions of information processing devices 10 and 10a may be provided in a SaaS (Software as a Service) format.

[0171] The present invention has been described above with reference to the embodiments, but the present invention is not limited to the above contents. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the invention.

[0172] For example, in Embodiments 2 and 3, the first user terminal 20 is a multifunction device with a signage, but the present invention is not limited thereto. For example, the first user terminal 20 may also be another image forming device with an external signage, a wireless LAN router, a smart speaker, or other communication device. Furthermore, for example, the first user terminal 20 may also be a terminal with communication capabilities integrated with the signage.

[0173] In the above-mentioned embodiments, the program can be stored using various types of non-transitory computer readable media and provided to the computer. Non-transitory computer readable media include various types of tangible recording media (tangible storage media). Examples of non-transitory computer readable media include magnetic recording media (e.g., floppy disks, magnetic tapes, hard disk drives), optical magnetic recording media (e.g., optical magnetic disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, DVDs (Digital Versatile Discs), semiconductor memories (e.g., mask ROMs, PROMs (Programmable Read-Only Memory), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory). Furthermore, the program can also be provided to the computer via various types of transitory computer readable media. Examples of transitory computer readable media include electric signals, optical signals, and electromagnetic waves. Transitory computer-readable media can provide the program to a computer via a wired communication path such as electric wires and optical fibers, or a wireless communication path.

[0174] A part or all of the above-mentioned embodiments may be described as the following supplementary notes, but are not limited to the following contents.

[0175] (Note 1)

[0176] An information processing system comprises a control unit, wherein the control unit executes the following steps: a first acquisition step of acquiring a plurality of first logs containing at least an IP address, a date, and a time from a first user terminal having a set inherent ID; a retrieval step of retrieving group information from a first database storing the inherent ID in association with group information, using the inherent ID of the first user terminal as a keyword; an inference step of inferring the IP address within the target period based on the regularity of the change in the IP address when there is a change in the IP address within a prescribed period in the plurality of first logs acquired; and a first storage step of storing in a second database at least information that corresponds the inferred IP address to the retrieved group information.

[0177] (Note 2)

[0178] According to the information processing system described in Note 1, the control unit performs the following second saving step: when there is no change in the IP address in the multiple first logs obtained within a specified period, the information that corresponds at least the IP address to the retrieved group information is saved as one record in the second database.

[0179] (Note 3)

[0180] An information processing system according to Note 1 or 2, wherein the control unit performs the following third saving step: when there is a change in the IP address in the multiple first logs obtained within a specified period, information that corresponds at least the IP address contained in the first log in which the IP address in the first log changed within the specified period to the retrieved group information is saved in the second database.

[0181] (Note 4)

[0182] An information processing system according to any one of Notes 1 to 3, wherein, in the inference step, the control unit determines whether the change is regular based on at least one of the number of times the same IP address appears within the prescribed period, the occurrence cycle of the IP address, and the variation range of the IP address.

[0183] (Note 5)

[0184] An information processing system according to any one of Notes 1 to 4, wherein the control unit performs the following steps: a second acquisition step of acquiring a second log containing at least an IP address when a second user terminal without a unique ID is accessed to a website, log information related to web page browsing, and an access date and time; and a generation step of determining, from the second database, group information corresponding to the IP address contained in the second log and corresponding to the access date and time, and generating information that corresponds at least the log information related to web page browsing, the access date and time, and the determined group information as analysis data.

[0185] (Note 6)

[0186] According to the information processing system described in Note 5, wherein the log information related to web page browsing includes information indicating a reference source and conversion, the control unit determines, for each group, a medium or access path that is effective for advertising to the group based on the log information corresponding to the group information of the group in the analysis data.

[0187] (Note 7)

[0188] An information processing system according to any one of Notes 1 to 4, wherein the control unit performs the following steps: a second acquisition step of acquiring a second log containing the IP address of the second user terminal when accessing the website, log information related to web page browsing, and the access date and time; a third acquisition step of acquiring a third log related to advertisement publishing and containing information related to the publishing date and time and the publishing content when the first user terminal has the function of publishing advertisements; and a judgment step of comparing the publishing date and time with the access date and time contained in the second log when the publishing content corresponding to the third log is associated with the website, and judging that there is a publishing effect when the comparison result meets the specified conditions, and the second user terminal is a terminal used by a user belonging to the group to which the first user terminal belongs and does not have a unique ID set.

[0189] (Note 8)

[0190] An information processing system according to any one of Notes 1 to 4, wherein the control unit performs the following steps: a second acquisition step of acquiring a second log containing the IP address of a second user terminal when accessing a website, log information related to web page browsing, and the date and time of access; a fourth acquisition step of acquiring a fourth log containing the IP address of a fourth user terminal when accessing a website, log information related to web page browsing, and the date and time of access; a comparison step of comparing the log information contained in the second log with the log information contained in the fourth log; and an output step of outputting a comparison result, wherein the second user terminal is a terminal used by a user belonging to a group to which the first user terminal belongs and does not have a set inherent ID, and the fourth user terminal is a terminal used by a user belonging to a group similar to the group to which the first user terminal belongs and does not have a set inherent ID.

[0191] (Note 9)

[0192] An information processing method is executed in a computer having a control unit, wherein the control unit executes the following steps: a first acquisition step of acquiring multiple first logs containing at least an IP address, a date, and a time from a first user terminal with a set inherent ID; a retrieval step of retrieving group information from a first database that stores the inherent ID in association with group information, using the inherent ID of the first user terminal as a keyword; an inference step of inferring the IP address within the target period based on the regularity of the change in the IP address when there is a change in the IP address within a specified period in the multiple first logs acquired; and a first storage step of storing information in a second database that corresponds at least the inferred IP address to the retrieved group information.

[0193] (Note 10)

[0194] A program for causing a computer to execute the following steps: a first acquisition step of acquiring a plurality of first logs containing at least an IP address, a date, and a time from a first user terminal having a set inherent ID; a retrieval step of retrieving group information from a first database storing the inherent ID in association with group information, using the inherent ID of the first user terminal as a keyword; an inference step of inferring the IP address within the target period based on the regularity of the change in the IP address when there is a change in the IP address within a specified period in the plurality of first logs acquired; and a first storage step of storing in a second database at least information that corresponds the inferred IP address to the retrieved group information.

[0195] Description of labels

[0196] 1.1a: System; 10.10a: Information processing device; 11: Control unit; 12: Processor; 13: ROM; 14: RAM; 15: Communication unit; 16: Storage unit; 17: Input unit; 18: Display unit; 20: First user terminal; 21: Control unit; 22: Processor; 23: ROM; 24: RAM; 25: Communication unit; 26: Storage unit; 27: Input unit; 28: Display unit; 29: Output unit; 30: Second user terminal; 31: Control unit; 32: Processor; 33: ROM; 34: RAM; 35: Communication unit; 36: Storage unit; 37: Input unit; 38: Display unit; 40: Log collection server; 50: Advertiser-side device; 60: Third user terminal; 111: First acquisition unit; 112: Retrieval unit; 113: Inference unit; 114: Registration unit; 115: Second acquisition unit; 116: Generation unit; 117: Analysis unit; 118: Third acquisition unit; 119: Comparison unit; 160: Measurement log DB; 161: First DB; 162: Second DB; 163: Third DB; 401: Site log DB; 1620: Determination table; 1621: Inference table; NW: Network.

Claims

1. An information processing system, wherein: The information processing system has: More than 1 processor; Memory; and More than 1 program, The one or more programs are stored in the memory and configured to be executed by the one or more processors. The one or more programs include instructions for executing the following: Acquire a plurality of first logs including at least an IP address and a date and time from a first user terminal to which a unique ID is set; Using the unique ID of the first user terminal as a keyword, searching for group information from a first database that stores the unique ID in association with group information; When there are changes in the IP addresses within a predetermined period in the plurality of first logs obtained, inferring the IP addresses within the target period based on the regularity of the changes in the IP addresses; as well as Information associating at least the inferred IP address with the retrieved group information is stored in the second database.

2. The information processing system according to claim 1, wherein The one or more programs further include instructions for saving, in the second database, at least one record corresponding to the IP address and the retrieved group information when there is no change in the IP address within a specified period in the plurality of first logs obtained.

3. The information processing system according to claim 1, wherein: The one or more programs also include the following instructions: when there is a change in the IP address in the multiple first logs obtained within a specified period, information is saved in the second database that corresponds to the IP address contained in the first log in which the IP address in the first log within the specified period has changed and the retrieved group information.

4. The information processing system according to claim 1, wherein: The one or more programs further include instructions for determining whether the variation is regular based on at least one of the number of times the same IP address appears within the predetermined period, the occurrence cycle of the IP address, and the variation range of the IP address during the estimation.

5. The information processing system according to claim 1, wherein: The one or more programs further include instructions for executing the following: Obtaining a second log including at least an IP address of a second user terminal without a unique ID accessing the website, log information related to web page browsing, and access date and time; From the second database, group information corresponding to the IP address contained in the second log and corresponding to the access date and time is determined, and information that corresponds at least the log information related to web page browsing, the access date and time, and the determined group information is generated as analysis data. The information processing system according to claim 5 , wherein: The log information related to web page browsing includes information indicating the reference source and conversion, The one or more programs further include instructions for estimating, for each group, a conversion level when an advertisement is distributed to the group, for each medium or access path, based on log information corresponding to group information of the group in the analytical data.

7. The information processing system according to claim 1, wherein: The one or more programs further include instructions for executing the following: Obtaining a second log including the IP address of the second user terminal when accessing the website, log information related to web page browsing, and access date and time; In the case where the first user terminal has a function of publishing advertisements, obtaining a third log related to advertisement publishing and including information related to publishing date and time and published content; and When the published content corresponding to the third log is associated with the website, the publishing date and time are compared with the access date and time included in the second log. When the comparison result meets the specified conditions, it is determined that the content has been published. The second user terminal is a terminal used by a user belonging to the group to which the first user terminal belongs and has no unique ID set.

8. The information processing system according to claim 1, wherein: The one or more programs further include instructions for executing the following: Obtaining a second log including the IP address of the second user terminal when accessing the website, log information related to web page browsing, and access date and time; Obtaining a fourth log including the IP address of the fourth user terminal when accessing the website, log information related to web page browsing, and access date and time; comparing the log information included in the second log with the log information included in the fourth log; as well as Output comparison results, The second user terminal is a terminal used by a user belonging to the group to which the first user terminal belongs and has no unique ID set. The fourth user terminal is a terminal used by a user belonging to a group different from the group to which the first user terminal belongs and has no unique ID set.

9. An information processing method, executed in a computer, wherein: In the computer, the information processing method includes the following contents: Acquire a plurality of first logs including at least an IP address and a date and time from a first user terminal to which a unique ID is set; Using the unique ID of the first user terminal as a keyword, searching for group information from a first database that stores the unique ID in association with group information; When there are changes in the IP addresses within a predetermined period in the plurality of first logs obtained, inferring the IP addresses within the target period based on the regularity of the changes in the IP addresses; as well as Information associating at least the inferred IP address with the retrieved group information is stored in the second database.

10. A non-transitory computer-readable medium storing one or more programs, wherein: The one or more programs include instructions that, when executed by a computer, cause the computer to: Acquire a plurality of first logs including at least an IP address and a date and time from a first user terminal to which a unique ID is set; Using the unique ID of the first user terminal as a keyword, searching for group information from a first database that stores the unique ID in association with group information; When there are changes in the IP addresses within a predetermined period in the plurality of first logs obtained, inferring the IP addresses within the target period based on the regularity of the changes in the IP addresses; as well as Information associating at least the inferred IP address with the retrieved group information is stored in the second database.

Images