Attribute value estimation device

Abstract

The present invention addresses the problem of estimating a user's attribute value without the need for the user to answer a questionnaire. An attribute value estimation device 1 is provided with: a storage unit 10 that stores relationship information regarding the relationship between an attribute value regarding a user and a terminal log obtained by a terminal 2 carried by the user; an acquisition unit 11 that acquires a terminal log of a target user; and an estimation unit 13 that estimates an attribute value of the target user on the basis of the target user's terminal log acquired by the acquisition unit 11 and the relationship information stored by the storage unit 10. The attribute value may relate to the cognitive function of the user. The attribute value may be the age of the user. The terminal log may be a log of the operation of the terminal 2 by the user, a log of the user's own actions, or a log of information based on location information of the terminal 2.

Description

[Technical Field]

[0001] One aspect of the present disclosure relates to an attribute value estimation device that estimates an attribute value related to a user. [Background technology]

[0002] The following Patent Document 1 discloses a plan proposal device that presents a questionnaire to a user to identify the user's attributes and acquires attribute data indicating the user's attributes by analyzing the responses obtained to the questionnaire. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-157578 Summary of the Invention [Problem to be solved by the invention]

[0004] In the above-described plan proposal device, the user needs to answer a questionnaire to acquire (estimate) attribute data indicating the user's attributes, which requires the user to take time and effort. Therefore, it is desired to estimate the user's attribute values ​​without the user having to answer a questionnaire. [Means for solving the problem]

[0005] An attribute value estimation device according to one aspect of the present disclosure includes a storage unit that stores related information relating to the relationship between an attribute value related to a user and a device log obtained by a device carried by the user, an acquisition unit that acquires the device log of a target user, and an estimation unit that estimates an attribute value of the target user based on the device log of the target user acquired by the acquisition unit and the related information stored by the storage unit.

[0006] In this aspect, the attribute value of the target user is estimated based on the acquired terminal log of the target user. That is, the attribute value of the user can be estimated without the user having to answer a questionnaire. [Effects of the Invention]

[0007] According to one aspect of the present disclosure, it is possible to estimate a user's attribute value without the user having to answer a questionnaire. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram illustrating an example of a system configuration of an attribute value estimation system including an attribute value estimation device according to an embodiment. [Figure 2] FIG. 1 is a diagram illustrating an example of a functional configuration of an attribute value estimation device according to an embodiment. [Figure 3] FIG. 10 is a diagram showing an example of distribution of age and screen-on count. [Figure 4] FIG. 10 is a diagram showing an example of a probability density distribution of age and the number of times the screen is turned on; [Figure 5] FIG. 10 is a diagram illustrating an example of a distribution of age and average screen-on time. [Figure 6] FIG. 10 is a diagram showing an example of a probability density distribution of age and average screen-on time. [Figure 7] FIG. 10 is a diagram illustrating an example of a distribution of age and total screen-on time. [Figure 8] FIG. 10 is a diagram illustrating an example of a probability density distribution of age and total screen-on time. [Figure 9] This is a diagram illustrating the age estimation method. [Figure 10] FIG. 10 is a diagram showing an example of visualization of estimated age. [Figure 11] 10 is a flowchart illustrating an example of a creation process executed by the attribute value estimation device according to the embodiment. [Figure 12] 10 is a flowchart illustrating an example of an estimation process executed by the attribute value estimation device according to the embodiment. [Figure 13]10 is a flowchart illustrating another example of the estimation process executed by the attribute value estimation device according to the embodiment. [Figure 14] FIG. 2 is a diagram illustrating an example of a hardware configuration of a computer used in the attribute value estimation device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicate explanations will be omitted. Furthermore, the embodiments of the present disclosure in the following description are specific examples of the present invention, and the present invention is not limited to these embodiments unless otherwise specified to limit the present invention.

[0010] Fig. 1 is a diagram showing an example of the system configuration of an attribute value estimation system 3 including an attribute value estimation device 1 (attribute value estimation device) according to an embodiment. As shown in Fig. 1, the attribute value estimation system 3 includes the attribute value estimation device 1 and one or more terminals 2 (terminals). The attribute value estimation device 1 and each terminal 2 are communicatively connected to each other via a network such as a mobile communication network, and can transmit and receive information to and from each other.

[0011] The attribute value estimation device 1 is a computer device that estimates attribute values ​​related to a user. The user may be a person who uses the attribute value estimation device 1 or a person under the control of the attribute value estimation device 1. An attribute value is a value of an attribute. An attribute may be a nature, characteristic, feature, feature, or property.

[0012] The attribute value for a user may be a value related to the cognitive function of the user. The attribute value for a user may be a value (representative value) indicating (representing) the cognitive function of the user. The attribute value for a user may be the age of the user. The attribute value for a user may be the brain age of the user. The attribute value for a user may be the IQ (Intelligence Quotient) of the user. The attribute value for a user may be the result of some kind of test being performed on the user. The attribute value for a user may be the score of a screening test for cognitive function (Mini-Mental State Examination).

[0013] The attribute value estimation device 1 will be described in detail later.

[0014] Terminal 2 is a computer device carried by a user. Terminal 2 obtains (acquires) a terminal log (terminal operation log), which is a log of the terminal. Terminal 2 may obtain the terminal log using a log collection application that is pre-installed on the terminal and collects the terminal log. Terminal 2 may obtain the terminal log based on various sensors and devices based on existing technology that are provided on the terminal. Examples of various sensors and devices include an acceleration sensor, a proximity sensor, an ambient light sensor, a temperature sensor, a humidity sensor, a barometric pressure sensor, a LiDAR scanner, a GPS (Global Positioning System), a device that performs wireless communication such as Wi-Fi (registered trademark), or a device that performs short-range wireless communication such as Bluetooth (registered trademark) or NFC (Near Field Communication). In the embodiment, terminal 2 is assumed to be a general smartphone that performs mobile communication, but is not limited thereto.

[0015] The terminal log may be a log of a user's operation of the terminal 2. Examples of the operation log include turning on / off the screen of the terminal 2, unlocking the terminal 2, or starting an app (application) on the terminal 2.

[0016] The terminal log may be a log of the actions of the user (carrying the terminal 2) himself / herself. Examples of the action log include the user's walking or the proximity of users to each other (for example, the user and another user).

[0017] The terminal log may be a log of information based on location information of terminal 2. The location information may be, for example, latitude and longitude acquired by a GPS equipped in terminal 2, or information related to location based on information obtained by a Wi-Fi (registered trademark) router or a base station device. Examples of a log of information based on location information include the living area (of the user carrying terminal 2) determined from the location information, or characteristics (of the user carrying terminal 2) obtained from the location information.

[0018] As described above, the terminal log may be a log of the user's operation of the terminal 2, a log of the user's own actions, or a log of information based on the location information of the terminal 2.

[0019] Terminal 2 may obtain multiple types of terminal logs (not limited to one type). For example, terminal 2 may obtain the number of times the screen is turned on, the average unlock time, the number of steps, and the living area calculated from the location information.

[0020] The terminal 2 may obtain (one or more types of) terminal logs periodically (for example, once per second) or at any timing. The terminal 2 may store (accumulate) the obtained (one or more types of) terminal logs inside the terminal 2. The terminal 2 may transmit the obtained or stored (one or more types of) terminal logs to the attribute value estimation device 1 periodically (for example, once per hour) or at any timing. When transmitting the terminal log to the attribute value estimation device 1, the terminal 2 may also transmit at least one of the attribute value of the user carrying the terminal 2 or identification information that identifies the terminal 2 or the user. In this case, the user's attribute value and identification information are assumed to be stored in the terminal 2 in advance.

[0021] Fig. 2 is a diagram showing an example of the functional configuration of the attribute value estimation device 1 according to the embodiment. As shown in Fig. 2, the attribute value estimation device 1 includes a storage unit 10 (storage unit), an acquisition unit 11 (acquisition unit), a creation unit 12 (creation unit), an estimation unit 13 (estimation unit), and a display unit 14 (display unit).

[0022] Each functional block of the attribute value estimation device 1 is assumed to function within the attribute value estimation device 1, but is not limited to this. For example, some of the functional blocks of the attribute value estimation device 1 may function in a computer device different from the attribute value estimation device 1 and connected to the attribute value estimation device 1 through a network, while appropriately transmitting and receiving information to and from the attribute value estimation device 1. Furthermore, some functional blocks of the attribute value estimation device 1 may be omitted, multiple functional blocks may be integrated into one functional block, or one functional block may be separated into multiple functional blocks.

[0023] Hereinafter, each function of the attribute value estimation device 1 shown in FIG. 2 will be described.

[0024] The storage unit 10 stores any information used in calculations in the attribute value estimation device 1 and the results of calculations in the attribute value estimation device 1. The information stored by the storage unit 10 may be referred to as appropriate by each function of the attribute value estimation device 1.

[0025] The storage unit 10 may (pre-store) attribute values ​​related to a user and (one or more types of) terminal logs obtained by the terminal 2 carried by the user. The storage unit 10 may store attribute values ​​related to a user acquired by an acquisition unit 11 described below, (one or more types of) terminal logs obtained by the terminal 2 carried by the user, and identification information for identifying the terminal 2 or the user.

[0026] The storage unit 10 may (in advance) store correspondence information that associates the terminal 2 carried by the user or identification information that identifies the user with attribute values ​​related to the user. Each functional block of the attribute value estimation device 1 can obtain the attribute values ​​related to the user from the terminal 2 carried by the user or the identification information that identifies the user by referring to the correspondence information stored by the storage unit 10.

[0027] The storage unit 10 stores related information relating to the relationship between attribute values ​​related to a user and terminal logs obtained by the terminal 2 carried by the user. The related information will be described in detail later. The storage unit 10 may store related information created by the creation unit 12 described later. The storage unit 10 may store multiple pieces of related information relating to the relationship between attribute values ​​related to a user and each of multiple types of terminal logs obtained by the terminal 2 carried by the user.

[0028] The acquisition unit 11 acquires the terminal log of the user. The acquisition unit 11 may acquire multiple types of terminal logs of the user. The acquisition unit 11 may acquire (one or more types of) terminal logs from the terminal 2 via a network. When acquiring (one or more types of) terminal logs of the user, the acquisition unit 11 may also acquire at least one of an attribute value of the user, or identification information that identifies the terminal 2 carried by the user or the user.

[0029] The acquisition unit 11 acquires a terminal log of a target user. The target user is a user whose attribute value is to be estimated. The acquisition unit 11 may acquire multiple types of terminal logs of the target user. The acquisition unit 11 may store the acquired (one or more types) of terminal logs in the storage unit 10, or may output the acquired terminal logs to the estimation unit 13.

[0030] Although the acquiring unit 11 is not normally expected to acquire the attribute values ​​of the target user or the terminal 2 carried by the target user or identification information identifying the target user, the acquiring unit 11 may acquire such values. In the case where the attribute values ​​are acquired, for example, the estimating unit 13 described below may output a comparison result between the acquired attribute values ​​and attribute values ​​estimated by the estimating unit 13, or the range of the estimation result may be controlled using the acquired attribute values ​​as parameters.

[0031] The creation unit 12 creates related information based on the attribute values ​​and (one or more types of) terminal logs of each of a plurality of users. The related information may be information about a probability density distribution. The related information may be information about a probability density distribution based on the attribute values ​​and frequencies (index values) related to the terminal logs.

[0032] 3 to 8, details of the creation of related information by the creation unit 12 will be described below. In the following description, the attribute value related to the user is assumed to be age, and the related information is assumed to be (information related to) a probability density distribution, but this is not limited to this.

[0033] First, the creation unit 12 creates (information relating to) a distribution of attribute values ​​and terminal logs (statistics) based on the attribute values ​​and (one or more types of) terminal logs of each of a plurality of users. More specifically, the creation unit 12 creates a distribution in which the x-axis (horizontal axis) represents the attribute values ​​and the y-axis (vertical axis) represents the frequency of terminal logs. Figure 3 is a diagram showing an example distribution of age and number of times the screen is turned on. The distribution example shown in Figure 3 is an example distribution in which the x-axis represents age and the y-axis represents the number of times the screen is turned on. Note that in the distribution example shown in Figure 3, the (graph) display of the number of times the screen is turned on by age is omitted, and instead the median by age is displayed. The line (graph) representing the median is not essential.

[0034] Here, a specific example of the frequency related to the terminal log will be described.

[0035] Examples of frequencies related to the log of the operation of terminal 2 by a user, which is a terminal log, include the screen on count, which is the number of times the screen of terminal 2 was turned on in a specified period; average screen on time, which is the average time (seconds) that the screen of terminal 2 was turned on in a specified period; total screen on time, which is the total time (seconds) that the screen of terminal 2 was turned on in a specified period; screen on / off count, which is the number of times the screen of terminal 2 was turned on / off in a specified period; average unlock time, which is the average time (seconds) that terminal 2 was unlocked in a specified period; total unlock time, which is the total time (seconds) that terminal 2 was unlocked in a specified period; number of app launches, which is the number of times an app (application) was launched on terminal 2 in a specified period; average app launch time, which is the average time (seconds) that an app was launched on terminal 2 in a specified period; or total app launch time, which is the total time (seconds) that an app was launched on terminal 2 in a specified period.

[0036] Examples of a log of a user's own behavior, which is a terminal log, include the number of steps taken by the user over a specified period (e.g., one day) (obtained based on an acceleration sensor on terminal 2, etc.), or the number of other users that the user came close to over a specified period (obtained based on a proximity sensor on terminal 2, etc.).

[0037] Examples of information logs based on location information, which are terminal logs, include the range of living, number of times going out, average distance from home, number of stay points, or trends in the number of people staying at the number of stay points.

[0038] A specific example of the frequency related to the terminal log has been described above.

[0039] Next, the creation unit 12 creates (information relating to) a probability density distribution based on the attribute value and the frequency (statistic) related to the terminal log, based on the above-mentioned distribution. More specifically, the creation unit 12 creates a probability density distribution in which the x-axis represents the attribute value and the y-axis represents the frequency related to the terminal log. FIG. 4 is a diagram showing an example of a probability density distribution between age and the number of times the screen is turned on. The example probability density distribution shown in FIG. 4 is an example probability density distribution in which the x-axis represents age and the y-axis represents the number of times the screen is turned on. FIG. 4 is an example probability density distribution created by the creation unit 12 based on the example distribution shown in FIG. 3. When the y-axis (frequency) is input in the probability density distribution, the x-axis (probability distribution of age) is obtained. The creation unit 12 may create a probability density distribution by aggregating the distribution based on the vertical axis. As can be seen from comparing the example distribution shown in FIG. 3 with the example probability density distribution shown in FIG. 4, the probability density distribution shown in FIG. 4 also has a similar shape along the median trendline of FIG. 3.

[0040] Similar to Figures 3 and 4, Figure 5 shows an example of a distribution of age and average screen-on time, and Figure 6 shows an example of a probability density distribution of age and average screen-on time. Similarly, Figure 7 shows an example of a distribution of age and total screen-on time, and Figure 8 shows an example of a probability density distribution of age and total screen-on time.

[0041] The calculation of the probability density distribution based on the above distribution is shown, for example, by the following formula.

number

[0042] The estimation unit 13 estimates the attribute value of the target user based on the device log of the target user acquired by the acquisition unit 11 and the related information stored by the storage unit 10. More specifically, the estimation unit 13 estimates the attribute value of the target user based on the device log of the target user stored by the storage unit 10 or the device log of the target user input by the acquisition unit 11 and the related information stored by the storage unit 10. For example, the estimation unit 13 estimates the age of the target user based on the number of times the screen of the target user is turned on and the probability density distribution of the age and the number of times the screen is turned on.

[0043] For example, based on the number of times the target user's screen is turned on and the probability density distribution of age and number of times the screen is turned on, the estimation unit 13 acquires a probability distribution (of age) of the row in the probability density distribution where the y-axis is the number of times the target user's screen is turned on, acquires the age with the highest probability from the acquired probability distribution, and estimates the acquired age as the age of the target user. In this way, the estimation unit 13 may perform estimation using a probability density distribution.

[0044] The estimation by the estimation unit 13 is performed, for example, on the following assumptions:

number

number

number

[0045] In the above formula, age i,est The formula above can be replaced with the following formula, which is the sum of each age and probability.

number

[0046] The estimation unit 13 may estimate an attribute value of the target user for each of multiple types of device logs of the target user acquired by the acquisition unit 11, based on the device log of that type and related information related to the device log of that type stored by the storage unit 10, and may estimate a final attribute value of the target user based on each estimated attribute value. More specifically, the estimation unit 13 may estimate an attribute value of the target user for each of multiple types of device logs of the target user stored by the storage unit 10 or multiple types of device logs of the target user input by the acquisition unit 11, based on the device log of that type and related information related to the device log of that type stored by the storage unit 10, and may estimate a final attribute value of the target user based on each estimated attribute value. For example, the estimation unit 13 (1) estimates the age of the target user based on the number of times the target user's screen is turned on and the probability density distribution of the age and the number of times the screen is turned on, (2) estimates the age of the target user based on the average screen on time of the target user and the probability density distribution of the age and the average screen on time, (3) estimates the age of the target user based on the total screen on time of the target user and the probability density distribution of the age and the total screen on time, and estimates the final attribute value of the target user based on the age estimated in (1), the age estimated in (2), and the age estimated in (3) (for example, the average of the three ages).

[0047] 9 is a diagram illustrating the age estimation method. As shown in FIG. 9, estimation unit 13 estimates age estimation result 1, which is the age of the target user, based on the number of times the target user's screen is turned on and off and the probability density distribution of the age and the number of times the screen is turned on and off, estimates age estimation result 2, which is the age of the target user, based on the average time to unlock the target user and the probability density distribution of the age and the average time to unlock, estimates age estimation result 3, which is the age of the target user, based on the number of steps taken per day and the probability density distribution of the age and the number of steps (per day), estimates age estimation result 4, which is the age of the target user, based on the living area obtained from the target user's location information and the probability density distribution of the age and the living area, ..., and calculates (estimates) an integrated age estimation result (final attribute value) based on (integrating) age estimation result 1, age estimation result 2, age estimation result 3, age estimation result 4, ...

[0048] The estimation unit 13 may output (transmit) the estimated (final) attribute value of the target user or at least one of the attribute values ​​estimated during the estimation (for example, the age estimated in (1), the age estimated in (2), and the age estimated in (3) above) to the target user's terminal 2 or another device via the communication device 1004 described below, or may output (display) it to an administrator of the attribute value estimation device 1 via the output device 1006 described below, or may store it in the storage unit 10, or may output it to the display unit 14.

[0049] The display unit 14 displays each attribute value estimated by the estimation unit 13 (the attribute value estimated during the estimation process). The display unit 14 may further display the final attribute value estimated by the estimation unit 13. FIG. 10 is a diagram illustrating a visualization example of estimated ages. In the visualization example illustrated in FIG. 10, the display unit 14 displays each attribute value described above at each item (vertex) in a radar chart, with the final attribute value displayed at the center. Specifically, at each vertex, "42" years old is displayed as the screen on / off tendency, "41" years old as the app usage tendency, "45" years old as the outing tendency, "62" years old as the step count tendency, and "55" years old as the unlock operation tendency. In this way, the display unit 14 may aggregate and visualize the data by type. Furthermore, "49" years old (the average value of each vertex) is displayed at the center as the (final) estimated age.

[0050] Next, an example of the creation process executed by the attribute value estimation device 1 will be described with reference to Fig. 11. Fig. 11 is a flowchart showing an example of the creation process executed by the attribute value estimation device according to the embodiment.

[0051] First, the creating unit 12 creates related information based on the attribute values ​​and terminal logs of each of a plurality of users (step S1), and then the storage unit 10 stores the related information created in S1 (step S2).

[0052] Next, an example of the estimation process executed by the attribute value estimation device 1 will be described with reference to Fig. 12. Fig. 12 is a flowchart showing an example of the estimation process executed by the attribute value estimation device according to the embodiment.

[0053] First, the acquisition unit 11 acquires the terminal log of the target user (step S10). Next, the estimation unit 13 estimates the attribute value of the target user based on the terminal log of the target user acquired in S10 and the related information stored by the storage unit 10 (step S11).

[0054] Next, another example of the estimation process executed by the attribute value estimation device 1 will be described with reference to Fig. 13. Fig. 13 is a flowchart showing another example of the estimation process executed by the attribute value estimation device according to the embodiment.

[0055] First, the acquisition unit 11 acquires multiple types of terminal logs of the target user (step S20). Next, the estimation unit 13 estimates an attribute value of the target user for each of the multiple types of terminal logs of the target user acquired in S20 based on the terminal log of that type and related information related to the terminal log of that type stored by the storage unit 10 (step S21). Next, the estimation unit 13 estimates a final attribute value of the target user based on the respective attribute values ​​estimated in S21 (step S22).

[0056] Next, the effects of the attribute value estimation device 1 according to the embodiment will be described.

[0057] The attribute value estimation device 1 includes a storage unit 10 that stores associated information relating to the association between attribute values ​​related to a user and a device log obtained by a device 2 carried by the user, an acquisition unit 11 that acquires the device log of a target user, and an estimation unit 13 that estimates the attribute value of the target user based on the device log of the target user acquired by the acquisition unit 11 and the associated information stored by the storage unit 10. With this configuration, the attribute value of the target user is estimated based on the acquired device log of the target user. In other words, the attribute value of a user can be estimated without the user having to answer a questionnaire.

[0058] Furthermore, in the attribute value estimation device 1, the attribute value may relate to the cognitive function of the user. With this configuration, it is possible to estimate the attribute value relating to the cognitive function of the target user.

[0059] Furthermore, in the attribute value estimation device 1, the attribute value may be the age of the user. With this configuration, the age of the target user can be estimated.

[0060] Furthermore, in the attribute value estimation device 1, the terminal log may be a log of the user's operation of the terminal 2, a log of the user's own actions, or a log of information based on location information of the terminal 2. With this configuration, the attribute value is estimated based on a more specific log, and therefore, a more accurate attribute value can be estimated.

[0061] Furthermore, the related information may relate to a probability density distribution in the attribute value estimation device 1. With this configuration, it is possible to estimate a more accurate attribute value based on the probability density distribution.

[0062] Furthermore, in the attribute value estimation device 1, the related information may relate to a probability density distribution based on the attribute value and the frequency related to the terminal log. With this configuration, it is possible to estimate a more accurate attribute value based on the probability density distribution based on the attribute value and the frequency related to the terminal log.

[0063] Furthermore, the attribute value estimation device 1 may further include a creation unit 12 that creates related information based on the attribute values ​​and terminal logs of each of a plurality of users, and the storage unit 10 may store the related information created by the creation unit 12. With this configuration, it is possible to estimate an attribute value that is more accurate and in line with the actual situation, for example, based on the related information created based on the latest attribute values ​​and terminal logs.

[0064] Furthermore, according to the attribute value estimation device 1, the storage unit 10 stores multiple pieces of related information relating to the association between attribute values ​​related to a user and each of multiple types of device logs obtained by the device 2 carried by the user, the acquisition unit 11 acquires multiple types of device logs of the target user, and the estimation unit 13 estimates an attribute value of the target user for each of the multiple types of device logs of the target user acquired by the acquisition unit 11 based on the device log of that type and the related information related to the device log of that type stored by the storage unit 10, and estimates a final attribute value of the target user based on each estimated attribute value. With this configuration, it is possible to estimate more accurate attribute values ​​based on multiple types of device logs.

[0065] Furthermore, the attribute value estimation device 1 may further include a display unit 14 that displays each attribute value estimated by the estimation unit 13. With this configuration, a user or an administrator of the attribute value estimation device 1 can easily check each estimated attribute value.

[0066] Furthermore, in the attribute value estimation device 1, the display unit 14 may further display the final attribute value estimated by the estimation unit 13. With this configuration, a user or an administrator of the attribute value estimation device 1 can easily check the estimated final attribute value.

[0067] The attribute value estimation device 1 estimates and evaluates age from a probability density distribution map of operation tendencies. The attribute value estimation device 1 makes it possible to estimate brain age, thereby providing healthcare guidance according to the deviation from ideal or actual age. The attribute value estimation device 1 estimates brain age using various behavioral data and probability distributions.

[0068] The purpose / background / challenge is that dementia is a disease that is difficult to cure once it develops, but early detection is also difficult, so efforts to prevent it are important. In order to generate motivation for prevention, it is necessary to objectively understand the state of one's own cognitive function (e.g., executive function, memory).

[0069] The attribute value estimation device 1 takes an approach of estimating and presenting a "brain age" to allow the user to objectively understand the state of cognitive function. Furthermore, brain age estimation does not require any special operations (such as taking a test), and brain age is estimated using smartphone logs. Alternatively, various logs collected in advance from many users of different ages through pre-installed apps or the like may be used to create a probability distribution of age for each data item, and ages may be estimated using the input data and averaged.

[0070] The attribute value estimation device 1 has the advantage of being able to estimate brain age using only smartphone usage trends, without requiring any special operations or tests. The attribute value estimation device 1 can estimate age using multiple automatically obtainable logs.

[0071] In conventional technology, it may be necessary to conduct a predetermined test (such as rock-paper-scissors), but this can be acquired automatically (through a smartphone log) with the attribute value estimation device 1. In conventional technology, it may be necessary to perform operations on the screen, but with the attribute value estimation device 1, it is not limited to operations on the screen and can also use activity information in the real world (number of steps or location information), etc.

[0072] The attribute value estimation device 1 of the present disclosure may have the following configuration.

[0073] [1] a storage unit for storing association information relating to associations between attribute values ​​related to a user and terminal logs obtained by a terminal carried by the user; an acquisition unit for acquiring a terminal log of a target user; an estimation unit that estimates an attribute value of the target user based on the terminal log of the target user acquired by the acquisition unit and the related information stored by the storage unit; An attribute value estimation device comprising:

[0074] [2] The attribute values ​​are related to the user's cognitive functions. [1] The attribute value estimation device according to [1].

[0075] [3] The attribute value is the user's age. [1] or [2]. An attribute value estimation device.

[0076] [4] The terminal log is a log of the user's terminal operation, a log of the user's own actions, or a log of information based on the terminal's location information. The attribute value estimation device according to any one of [1] to [3].

[0077] [5] The relevant information is about probability density distributions, The attribute value estimation device according to any one of [1] to [4].

[0078] [6] The related information is about a probability density distribution based on the attribute value and the frequency of the terminal log. The attribute value estimation device according to any one of [1] to [5].

[0079] [7] a creation unit that creates related information based on the attribute values ​​and terminal logs of each of the plurality of users; the storage unit stores the related information created by the creation unit. The attribute value estimation device according to any one of [1] to [6].

[0080] [8] the storage unit stores a plurality of pieces of association information relating to associations between attribute values ​​related to a user and each of a plurality of types of terminal logs obtained by a terminal carried by the user; the acquisition unit acquires multiple types of terminal logs of the target user; the estimation unit estimates an attribute value of the target user for each of the multiple types of terminal logs of the target user acquired by the acquisition unit based on the terminal log of that type and related information related to the terminal log of that type stored by the storage unit, and estimates a final attribute value of the target user based on each estimated attribute value; The attribute value estimation device according to any one of [1] to [7].

[0081] [9] a display unit that displays each attribute value estimated by the estimation unit, [8] The attribute value estimation device according to [8].

[0082]

[10] the display unit further displays the final attribute value estimated by the estimation unit. [9] The attribute value estimation device according to [9].

[0083] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wires, wirelessly, etc.) and these multiple devices. The functional block may also be realized by combining the single device or multiple devices with software.

[0084] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocation, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0085] For example, the attribute value estimation device 1 according to an embodiment of the present disclosure may function as a computer that performs processing of the attribute value estimation method of the present disclosure. Fig. 14 is a diagram showing an example of the hardware configuration of the attribute value estimation device 1 according to an embodiment of the present disclosure. The attribute value estimation device 1 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0086] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the attribute value estimation apparatus 1 may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0087] Each function in the attribute value estimation device 1 is realized by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communication via the communication device 1004, and control at least one of reading and writing data in the memory 1002 and storage 1003.

[0088] The processor 1001 controls the entire computer by running, for example, an operating system. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. For example, the above-mentioned acquisition unit 11, creation unit 12, estimation unit 13, etc. may be realized by the processor 1001.

[0089] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with the programs. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. For example, the acquisition unit 11, creation unit 12, and estimation unit 13 may be implemented by a control program stored in the memory 1002 and running on the processor 1001, and similar implementations may be made for other functional blocks. While the above-described various processes have been described as being executed by one processor 1001, they may also be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may also be transmitted from a network via a telecommunications line.

[0090] The memory 1002 is a computer-readable recording medium and may be configured, for example, by at least one of a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0091] Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0092] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, or a communication module. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). For example, the above-mentioned acquisition unit 11, creation unit 12, estimation unit 13, etc. may be realized by the communication device 1004.

[0093] The input device 1005 is an input device (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (for example, a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (for example, a touch panel).

[0094] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0095] The attribute value estimation device 1 may also be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0096] Notification of information is not limited to the aspects / embodiments described in this disclosure, and may be performed using other methods.

[0097] Each aspect / embodiment described in the present disclosure may be applied to at least one of systems using LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), FRA (Future Radio Access), NR (New Radio), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark), IEEE 802.20, UWB (Ultra-Wideband), Bluetooth (registered trademark), or other appropriate systems, and next-generation systems extended based on these. Furthermore, a combination of multiple systems (e.g., a combination of at least one of LTE and LTE-A with 5G, etc.) may also be applied.

[0098] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0099] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0100] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0101] Each aspect / embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Furthermore, notification of predetermined information (e.g., notification that "X is true") is not limited to being done explicitly, but may be done implicitly (e.g., by not notifying the predetermined information).

[0102] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0103] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0104] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0105] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0106] In addition, terms explained in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings.

[0107] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0108] Furthermore, the information, parameters, etc. described in this disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information.

[0109] The names used for the above parameters are not limiting in any way, and furthermore, the mathematical formulas etc. using these parameters may differ from those explicitly disclosed in this disclosure.

[0110] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0111] The terms "connected," "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using one or more wires, cables, and / or printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

[0112] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0113] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0114] The "means" in the configuration of each of the above devices may be replaced with "part," "circuit," "device," etc.

[0115] When used in this disclosure, the terms "include," "including," and variations thereof are intended to be inclusive, similar to the term "comprising." Furthermore, when used in this disclosure, the term "or" is not intended to be an exclusive or.

[0116] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0117] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different." [Explanation of symbols]

[0118] 1...attribute value estimation device, 2...terminal, 3...attribute value estimation system, 10...storage unit, 11...acquisition unit, 12...creation unit, 13...estimation unit, 14...display unit, 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus.

Claims

1. a storage unit for storing a plurality of pieces of association information relating to associations between attribute values ​​related to a user and each of a plurality of types of terminal logs obtained by a terminal carried by the user; an acquisition unit that acquires multiple types of terminal logs of a target user; an estimation unit that estimates an attribute value of the target user for each of multiple types of terminal logs of the target user acquired by the acquisition unit based on the terminal log of that type and related information related to the terminal log of that type stored by the storage unit, and estimates a final attribute value of the target user based on each estimated attribute value; An attribute value estimation device comprising:

2. The attribute values ​​are related to the user's cognitive functions. The attribute value estimation device according to claim 1 .

3. The attribute value is the user's age. The attribute value estimation device according to claim 1 .

4. The terminal log is a log of the user's terminal operation, a log of the user's own actions, or a log of information based on the terminal's location information. The attribute value estimation device according to claim 1 .

5. The relevant information is about probability density distributions, The attribute value estimation device according to claim 1 .

6. The related information is about a probability density distribution based on the attribute value and the frequency of the terminal log. The attribute value estimation device according to claim 1 .

7. a creation unit that creates related information based on the attribute values ​​and terminal logs of each of the plurality of users; the storage unit stores the related information created by the creation unit. The attribute value estimation device according to claim 1 .

8. a display unit that displays each attribute value estimated by the estimation unit, The attribute value estimation device according to claim 1 .

9. the display unit further displays the final attribute value estimated by the estimation unit. The attribute value estimation device according to claim 8 .

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