Information browsing ability estimation device, information browsing ability estimation method, and program

Abstract

To provide a technology of more accurately estimating a user's ability to browse information.SOLUTION: An information browsing capacity estimation device comprises an estimation unit that estimates the information browsing ability of a second user, based on browsing management data including one or more information browsing histories of a first user, behavioral data including one or more behavioral histories of the first user, and second user behavior.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information browsing ability estimation device, an information browsing ability estimation method, and a program. [Background technology]

[0002] In order to increase users' attention or interest in information, personalized information based on the user's situation may be notified to the user terminal. For example, a technology has been disclosed in which appropriate advertising information is notified to a user group targeted by an advertiser (for example, women with an open rate of 20% or more) based on user attribute information (for example, age, sex, interests, etc.) and the open rate of messages distributed in a specified area (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-156460 Summary of the Invention [Problem to be solved by the invention]

[0004] However, it would be desirable to provide a technique that estimates a user's information viewing ability with greater accuracy. [Means for solving the problem]

[0005] In order to solve the above problem, according to one aspect of the present invention, there is provided a system including an estimation unit that estimates an information browsing ability of a second user based on browsing management data including one or more information browsing histories of a first user, behavior data including one or more behavior histories of the first user, and behavior of a second user. each of the information browsing histories includes a browsing time, which is the time when first notification information transmitted to the terminal of the first user is viewed by the first user, and a notification time, which is the time when the first notification information is transmitted to the terminal of the first user; the estimation unit calculates the information browsing ability of the first user based on the browsing management data, estimates the information browsing ability of the second user based on the information browsing ability of the first user, the behavior data, and the behavior of the second user, and calculates the information browsing ability of the first user corresponding to a time after the notification time and before the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time; An information browsing ability estimation device is provided.

[0010] The estimation unit may calculate the information browsing ability of the first user corresponding to a time after the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time. The estimation unit may calculate the information viewing ability of the first user corresponding to a time later than the notification time and earlier than the viewing time to be lower than the information viewing ability of the first user corresponding to a time later than the viewing time.

[0011] The estimation unit may generate information viewing ability data including one or more behavioral conditions according to the behavioral data and the information viewing ability of the first user corresponding to each of the behavioral conditions, and estimate the information viewing ability of the second user based on the information viewing ability data and the behavior of the second user.

[0012] The estimation unit extracts, as extracted data, information browsing ability of the first user corresponding to a behavioral condition satisfied by the behavior of the second user from the information browsing ability data, and average A value may be estimated as the second user's information viewing ability.

[0014] The estimation unit may generate an inference model using a machine learning algorithm based on the information viewing ability of the first user and the behavioral data, and estimate the information viewing ability of the second user based on the inference model and the behavior of the second user.

[0015] The viewing time included in at least a portion of the information viewing history may be associated with an acceptance level input by the first user for the first notification information, and the estimation unit may calculate the information viewing ability of the first user corresponding to the viewing time associated with the acceptance level based on the acceptance level.

[0016] The information browsing ability estimation device may include an information notification unit that notifies the terminal of the second user of second notification information based on the information browsing ability of the second user being greater than a predetermined value.

[0017] Each of the behavioral histories of the first user may include at least one of the location where the first user was present, the time when the first user was present, the type of activity of the first user, and the weather at the location where the first user was present.

[0018] The first user may include one or more users, the second user may include one or more users, and the first user and the second user may have a common user.

[0019] The first user may include one or more users, the second user may include one or more users, and the first user and the second user may not have a common user.

[0020] The first user and the second user may belong to the same group.

[0021] According to another aspect of the present invention, the method includes estimating the information browsing ability of the second user based on browsing management data including one or more information browsing histories of the first user, behavioral data including one or more behavioral histories of the first user, and behavior of the second user. An information browsing ability estimation method executed by a computer, wherein each of the information browsing histories includes a browsing time, which is a time when first notification information transmitted to a terminal of the first user is browsed by the first user, and a notification time, which is a time when the first notification information is transmitted to the terminal of the first user; the computer calculates the information browsing ability of the first user based on the browsing management data; estimates the information browsing ability of the second user based on the information browsing ability of the first user, the behavior data, and the behavior of the second user; and calculates the information browsing ability of the first user corresponding to a time after the notification time and before the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time. A method for estimating information browsing ability is provided.

[0022] According to another aspect of the present invention, a computer includes an estimation unit that estimates an information browsing ability of a second user based on browsing management data including one or more information browsing histories of a first user, behavior data including one or more behavior histories of the first user, and behavior of the second user. each of the information browsing histories includes a browsing time, which is the time when first notification information transmitted to the terminal of the first user is viewed by the first user, and a notification time, which is the time when the first notification information is transmitted to the terminal of the first user; the estimation unit calculates the information browsing ability of the first user based on the browsing management data, estimates the information browsing ability of the second user based on the information browsing ability of the first user, the behavior data, and the behavior of the second user, and calculates the information browsing ability of the first user corresponding to a time after the notification time and before the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time; A program is provided that functions as an information browsing ability estimation device. [Effects of the Invention]

[0023] As described above, the present invention provides a technique for estimating a user's information viewing ability with higher accuracy. [Brief explanation of the drawings]

[0024] [Figure 1] 1 is a diagram illustrating an example of the configuration of an information notification system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram illustrating the operation of the information notification system according to the embodiment. [Figure 3] FIG. 10 is a diagram illustrating an example of viewing management data. [Figure 4] FIG. 10 is a diagram illustrating an example of behavior data. [Figure 5] FIG. 10 is a diagram illustrating an example of information browsing ability data. [Figure 6] FIG. 10 is a diagram illustrating the operation of an information notification unit. [Figure 7] FIG. 2 is a diagram illustrating a hardware configuration of an information processing device as an example of the information browsing ability estimation device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0025] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant explanations will be omitted.

[0026] Furthermore, in this specification and drawings, multiple components having substantially the same functional configuration may be distinguished by adding different numbers after the same reference numeral. However, if there is no particular need to distinguish between multiple components having substantially the same functional configuration, only the same reference numeral will be used. Furthermore, similar components in different embodiments may be distinguished by adding different letters after the same reference numeral. However, if there is no particular need to distinguish between similar components in different embodiments, only the same reference numeral will be used.

[0027] <0. Overview> First, an outline of the embodiment of the present invention will be described.

[0028] In order to increase users' attention or interest in information, personalized information based on the user's situation may be notified to the user terminal. For example, a technology has been disclosed in which appropriate advertising information is notified to a user group targeted by an advertiser (for example, women with an open rate of 20% or more) based on user attribute information (for example, age, sex, interests, etc.) and the open rate of messages distributed in a specified area (see, for example, Patent Document 1).

[0029] However, the above technology has the problem that it is not effective enough to increase the likelihood that a user will open and view the notified information. Furthermore, the above technology has the problem that notifications of information that are not opened reduce user satisfaction or reduce network utilization efficiency.

[0030] Therefore, in an embodiment of the present disclosure, a technology is proposed for estimating with higher accuracy a user's ability to browse information (hereinafter also referred to as "information browsing ability"). Note that information browsing ability can also be expressed as the ease with which information can be browsed by a user.

[0031] As an example, an embodiment of the present disclosure proposes a technology that estimates a user's information viewing ability based on each user's behavioral pattern (for example, a behavioral pattern in which a user is more likely to view information output from a smartphone while sitting in an office (such as from 12:00 to 13:00 on weekdays)).

[0032] This technology can estimate a user's information viewing ability with high accuracy, and by notifying the user of information based on the estimated information viewing ability, the likelihood that the user will open and view the information can be increased.

[0033] The outline of the embodiment of the present invention has been described above.

[0034] <1. Details of the embodiment> Next, details of the embodiment of the present invention will be described.

[0035] [1-1. Description of the configuration] An example of the configuration of an information notification system according to an embodiment of the present invention will be described.

[0036] Fig. 1 is a diagram showing an example of the configuration of an information notification system according to an embodiment of the present invention. As shown in Fig. 1, the information notification system 1 according to the embodiment of the present invention includes an information browsing ability estimation device 10 and a user terminal 20. The information browsing ability estimation device 10 and the user terminal 20 are connected to a network, and are configured to be able to communicate with each other via the network.

[0037] (Information browsing ability estimation device 10) The information browsing ability estimation device 10 can be realized by a computer. The information browsing ability estimation device 10 includes a control unit (not shown) and a storage unit (not shown). The control unit (not shown) includes a browsing history output unit 120, a behavior history output unit 130, an information browsing ability estimation unit 140, and an information notification unit 160. The storage unit (not shown) includes an information browsing ability accumulation unit 150.

[0038] The control unit (not shown) is realized by a processor executing a program. The program may be recorded on a recording medium and read from the recording medium and executed by the processor. Alternatively, these blocks may be configured by dedicated hardware.

[0039] The storage unit (not shown) may be configured with a memory, such as a random access memory (RAM), a hard disk drive, or a flash memory.

[0040] (Viewing history output unit 120) The browsing history output unit 120 acquires the information notification data and the opening response data output from the information notification unit 160. The browsing history output unit 120 obtains the browsing management data based on the information notification data and the opening response data. Then, the browsing history output unit 120 outputs the browsing management data to the information browsing ability estimation unit 140.

[0041] (Behavioral history output unit 130) The behavior history output unit 130 acquires user situation data output from the user terminal 20. The behavior history output unit 130 obtains behavior data based on the user situation data. The behavior history output unit 130 outputs the behavior data to the information browsing ability estimation unit 140.

[0042] (Information browsing ability estimation unit 140) The information browsing ability estimation unit 140 acquires the behavioral data output from the behavior history output unit 130. The information browsing ability estimation unit 140 also acquires the browsing management data output from the browsing history output unit 120. The information browsing ability estimation unit 140 calculates the information browsing ability of the user based on the browsing management data. Then, the information browsing ability estimation unit 140 obtains the information browsing ability data based on the information browsing ability and the behavioral data.

[0043] The information browsing ability estimation unit 140 stores the information browsing ability data in the information browsing ability storage unit 150 .

[0044] When an information notification request to a user is output from information notification unit 160, information browsing ability estimation unit 140 acquires information browsing ability data of the user from information browsing ability accumulation unit 150. Information browsing ability estimation unit 140 estimates the user's current information browsing ability based on the information browsing ability data acquired from information browsing ability accumulation unit 150 and the user's current behavioral data. Information browsing ability estimation unit 140 outputs the user's current information browsing ability to information notification unit 160.

[0045] (Information browsing capability storage unit 150) The information browsing ability accumulation unit 150 stores the information browsing ability data output from the information browsing ability estimation unit 140. In addition, the information browsing ability accumulation unit 150 outputs the stored information browsing ability data to the information browsing ability estimation unit 140.

[0046] (Information Notification Department 160) The information notification unit 160 generates an information notification request for the user at any timing and outputs the information notification request to the information browsing ability estimation unit 140. The information notification unit 160 acquires the user's current information browsing ability output from the information browsing ability estimation unit 140 based on the information notification request, and transmits a message (notification information) to the user terminal 20 via the communication interface based on the user's current information browsing ability.

[0047] The information notification unit 160 outputs information notification data corresponding to the transmission of the message to the user terminal 20 to the browsing history output unit 120. Furthermore, the information notification unit 160 acquires opening response data corresponding to the transmission of the message to the user terminal 20 from the user terminal 20. Then, the information notification unit 160 outputs the information notification data and the opening response data to the browsing history output unit 120.

[0048] (User terminal 20) User terminal 20 may be realized by a computer. When user terminal 20 receives a message output from information notification unit 160, it outputs opening response data corresponding to the reception of the message to information notification unit 160. User terminal 20 also outputs user situation data to behavior history output unit 130. For example, user terminal 20 may be a terminal carried by the user.

[0049] In the embodiment of the present invention, an example is mainly assumed in which the browsing history output unit 120, the behavior history output unit 130, the information browsing ability estimation unit 140, and the information notification unit 160 are configured by a single server connected to the user terminal 20. However, as will be explained later, these functions do not have to be configured by a single server.

[0050] The above has described an example of the configuration of the information notification system 1 according to the embodiment of the present invention.

[0051] [1-2. Explanation of operation] Next, an example of the operation of the information notification system 1 according to the embodiment of the present invention will be described.

[0052] Fig. 2 is a diagram for explaining the operation of the information notification system 1 according to the embodiment of the present invention. As shown in Fig. 2, the operation of the information notification system 1 according to the embodiment of the present invention can be divided into the following steps: (S1) acquisition of browsing management data and behavior data, (S2) update of information browsing ability data, (S3) confirmation of information notification request, (S4) estimation of information browsing ability, (S5) determination of the magnitude of information browsing ability, and (S6) information notification.

[0053] Each of these steps will be described in turn below.

[0054] (S1) Acquisition of browsing management data and behavioral data The browsing history output unit 120 acquires the information notification data and the opening response data output from the information notification unit 160. Here, the information notification data is data in which the time when the information notification unit 160 sent a message to the user terminal 20 is associated with a user ID indicating the user. The opening response data is data in which the time when the user terminal 20 opened the message by a user operation is associated with a user ID indicating the user.

[0055] In an embodiment of the present invention, the opening of a message by the user terminal 20 can also be considered as the user viewing the message. In other words, the opening time can also be referred to as the viewing time. If the user leaves the message unopened, no opening response data will be present. Furthermore, when a user uses the system for the first time, no information notification data or opening response data will be present.

[0056] The browsing history output unit 120 obtains browsing management data based on the information notification data and the opening response data. When the browsing history output unit 120 obtains new browsing management data that does not exist in the already stored browsing management data, the browsing history output unit 120 outputs the newly obtained browsing management data to the information browsing ability estimation unit 140. The browsing history output unit 120 stores the newly obtained browsing management data.

[0057] FIG. 3 is a diagram showing an example of viewing management data. As shown in FIG. 3, the viewing management data includes one or more information viewing histories in which a "user ID," a "notification time," and a "opening time" are associated with each other. That is, each row in FIG. 3 may correspond to an information viewing history. Here, the "user ID" is a user ID that is commonly included in the information notification data and the opening response data. The "notification time" is the time included in the information notification data, and the "opening time" is the time included in the opening response data.

[0058] 3 shows only the information browsing history of the user with the user ID "123" as the browsing management data. However, the information browsing history of users corresponding to other user IDs may also be included in the browsing management data.

[0059] The behavior history output unit 130 acquires the user situation data output from the user terminal 20. Here, the user situation data is data indicating the situation of the user.

[0060] For example, the user terminal 20 may manage a user ID and the time the user was present, and include these in the user situation data. The user terminal 20 may also manage location data detected by a location device, such as a radio wave receiver from a beacon installed indoors or outdoors and / or a GPS (Global Positioning System) sensor, and include these in the user situation data. The user terminal 20 may also manage the number of steps detected by a pedometer or the like, and / or the usage status of a built-in microphone (hereinafter also referred to as "built-in microphone") (for example, information indicating whether the built-in microphone is being used), and include these in the user situation data.

[0061] The behavior history output unit 130 obtains behavior data based on the user situation data. For example, the behavior history output unit 130 obtains, as the behavior data, a user ID, a time when the user was present, a location where the user was present, a type of activity of the user, and the weather at the location where the user was present.

[0062] For example, the behavior history output unit 130 may detect the location of the user (e.g., where in a building the user is, whether the user is at home, whether the user is outdoors, etc.) based on the location data included in the user situation data. For example, the location of the user in a building may be detected based on the reception results of radio waves from a beacon. Furthermore, the location of the user at home or outdoors may be detected based on the detection results from a GPS sensor or based on the number of steps. For example, if the number of steps of the user has increased beyond a threshold since the user was at home, the user may be determined to be outdoors. Alternatively, if the number of steps of the user has not increased beyond a threshold since the user was at home, the user may be determined to be at home.

[0063] Furthermore, the behavior history output unit 130 may detect an activity type (e.g., desk work, walking, rest, remote conference, etc.) based on the number of steps, the usage status of the built-in microphone, and location data included in the user situation data. For example, if the number of steps taken by the user per unit time is less than a first threshold, the activity type may be determined to be desk work. If the number of steps taken by the user per unit time is more than a second threshold, the activity type may be determined to be walking. If the user is located in a rest area, the activity type may be determined to be rest. If the built-in microphone is being used (or if a conference application is running), the activity type may be determined to be a remote conference.

[0064] Furthermore, the behavior history output unit 130 may use an external weather service to detect the weather at the location where the user was located, based on the location data (detected based on the detection results by the GPS sensor) included in the user situation data.

[0065] Fig. 4 is a diagram showing an example of behavioral data. As shown in Fig. 4, the behavioral data includes one or more behavioral histories in which a "user ID," a "time" when the user was present, a "location" when the user was present, a "type of activity" of the user, and the "weather" at the location where the user was present are associated with each other. In other words, each row in Fig. 4 may correspond to a behavioral history.

[0066] The behavioral history does not have to include all of "time," "place," "activity type," and "weather." For example, the behavioral history may include at least some of "time," "place," "activity type," and "weather." Alternatively, the behavioral history may include history related to behaviors other than "time," "place," "activity type," and "weather."

[0067] 4 shows only the behavioral history of the user with the user ID "123" as behavioral data. However, the behavioral history of users corresponding to other user IDs may also be included in the behavioral data.

[0068] When newly obtained behavioral data that does not exist in the behavioral data that has already been accumulated, the behavior history output unit 130 outputs the newly obtained behavioral data to the information browsing ability estimation unit 140. Then, the behavior history output unit 130 accumulates the newly obtained behavioral data.

[0069] After the acquisition of the browsing management data and the behavior data (S1) is executed, the operation of the information notification system 1 shifts to updating the information browsing ability data (S2).

[0070] (S2) Update of information browsing ability data The information browsing ability estimation unit 140 acquires the behavioral data output from the behavior history output unit 130. The information browsing ability estimation unit 140 also acquires the browsing management data output from the browsing history output unit 120. The information browsing ability estimation unit 140 is triggered by acquiring the browsing management data, and calculates the information browsing ability of the user based on the browsing management data.

[0071] For example, it can be assumed that the user's information browsing ability is higher at the time of opening compared to times other than the time of opening.

[0072] Therefore, the information browsing ability estimation unit 140 may calculate the information browsing ability of a user corresponding to a time after the notification time and before the opening time to be lower than the information browsing ability of a user corresponding to the opening time. Also, the information browsing ability estimation unit 140 may calculate the information browsing ability of a user corresponding to a time after the opening time to be lower than the information browsing ability of a user corresponding to the opening time.

[0073] As an example, the information browsing ability estimation unit 140 may calculate the information browsing ability corresponding to the time period from the notification time to the opening time as -1 (low ability). Furthermore, the information browsing ability estimation unit 140 may calculate the information browsing ability corresponding to the time period of the opening time as +1 (high ability). Furthermore, the information browsing ability estimation unit 140 may calculate the information browsing ability corresponding to other time periods as 0 (neither).

[0074] Then, the information browsing ability estimation unit 140 obtains information browsing ability data based on the information browsing ability and the behavioral data. The information browsing ability estimation unit 140 stores the information browsing ability data in the information browsing ability storage unit 150. For example, the information browsing ability estimation unit 140 generates information browsing ability data including one or more behavioral conditions according to the behavioral data and information browsing abilities corresponding to each of the behavioral conditions.

[0075] FIG. 5 is a diagram showing an example of information browsing ability data. The information browsing ability data shown in FIG. 5 is an example of information browsing ability data corresponding to the browsing management data shown in FIG. 3 and the behavioral data shown in FIG. 4. Referring to FIG. 5, the information browsing ability data includes one or more behavioral conditions that correspond to a "user ID," a "weekday / holiday classification," a "time period," a "location," an "activity type," a "weather," and an "information browsing ability." In other words, each row in FIG. 5 may correspond to a behavioral condition.

[0076] For example, the information browsing ability estimation unit 140 sets the behavior conditions "weekday / holiday classification" and "time period" based on the behavior history "time" included in the behavior data shown in FIG. 4. More specifically, the information browsing ability estimation unit 140 classifies the days included in the behavior history "time" into "weekday / holiday classification" and sets a similarity range (e.g., ±α) based on the time included in the behavior history "time" as the "time period." For example, α may be 10 minutes. The "weekday / holiday classification" may be determined uniformly regardless of the user, or may vary depending on the user.

[0077] Furthermore, the information browsing ability estimation unit 140 sets the behavior history "location" included in the behavior data shown in Fig. 4 as the behavior condition "location." Furthermore, the information browsing ability estimation unit 140 sets the behavior history "activity type" included in the behavior data shown in Fig. 4 as the behavior condition "activity type." Furthermore, the information browsing ability estimation unit 140 sets the behavior history "weather" included in the behavior data shown in Fig. 4 as the behavior condition "weather."

[0078] As with the behavior history, the behavior conditions do not have to include all of the "weekday / holiday classification," "time period," "location," "activity type," and "weather." For example, the behavior conditions may include at least some of the "weekday / holiday classification," "time period," "location," "activity type," and "weather." Alternatively, the behavior conditions may include conditions related to behavior other than the "weekday / holiday classification," "time period," "location," "activity type," and "weather."

[0079] In the example shown in Fig. 3, the user did not open any messages during the time period from after 13:00 on September 27th to before 15:00 on the same day. Therefore, as shown in Fig. 5, the information browsing ability corresponding to each time period from 13:02 on September 27th to 14:58 on the same day may be calculated as -1.

[0080] Furthermore, at 15:00 on the same day, the user opened the message. Therefore, as shown in Figure 5, the information viewing ability corresponding to the same time slot can be calculated as +1.

[0081] Furthermore, no message was notified during the time period from after 15:00 on the same day until before 15:04 on the same day. Therefore, as shown in Figure 5, the information viewing ability corresponding to the time period of 15:02 on the same day may be calculated as 0.

[0082] It is also possible that a message is not opened even after a certain period of time (e.g., three hours) has passed since the message was notified. In such a case, the information browsing ability estimation unit 140 may calculate the information browsing ability corresponding to each time period by regarding the time after the notification time as the opening time.

[0083] For example, the information browsing ability estimation unit 140 stores information browsing ability data including one or more behavioral conditions and information browsing abilities corresponding to each of the behavioral conditions in the information browsing ability accumulation unit 150. This updates the information browsing ability data accumulated in the information browsing ability accumulation unit 150.

[0084] After the information browsing ability data is updated (S2), the operation of the information notification system 1 proceeds to confirming the information notification request (S3). Note that if the browsing management data is not acquired by the information browsing ability estimation unit 140, the operation of the information notification system 1 may proceed to confirming the information notification request (S3) without updating the information browsing ability data (S2).

[0085] (S3) Confirmation of information notification request The information notification unit 160 determines whether or not the present is a predetermined timing for notifying a message (hereinafter also referred to as "notification timing"). If the information notification unit 160 determines that the present is the notification timing, it generates an information notification request and outputs the generated information notification request to the information browsing ability estimation unit 140. Here, the notification timing is not limited.

[0086] For example, the notification may be given when the current time is the time when the user is heading to work and when there are stairs or an escalator within a predetermined distance from the user's current location. In this case, the message given to the user may be a message encouraging the user to use the stairs. Such a message may be an example of a message encouraging the user to engage in healthy behavior.

[0087] Alternatively, the notification may be sent when the current weather is clear, the current time is the user's lunch break (e.g., from 12:00 to 13:00), and the user's number of steps that day is less than a predetermined number. In this case, the message sent to the user may be a message encouraging the user to take a walk. Such a message may be an example of a message encouraging the user to engage in healthy behavior.

[0088] Alternatively, the notification may be sent when the user is in a rest area and an acquaintance of the user is also in the same rest area. In this case, the message sent to the user may be a message encouraging the user to talk to the acquaintance. Such a message may be an example of a message encouraging the user to interact with others.

[0089] After the information notification request is output to the information browsing ability estimation unit 140, the operation of the information notification system 1 shifts to (S4) estimating information browsing ability. On the other hand, if it is determined that the current timing is not the timing for notification, the operation of the information notification system 1 shifts to (S1) acquiring browsing management data and behavioral data.

[0090] (S4) Estimation of information browsing ability When an information notification request to a user is output from information notification unit 160, information browsing ability estimation unit 140 acquires information browsing ability data of the user from information browsing ability accumulation unit 150. Information browsing ability estimation unit 140 estimates the user's current information browsing ability based on the information browsing ability data acquired from information browsing ability accumulation unit 150 and the user's current behavioral data.

[0091] More specifically, the information browsing ability estimation unit 140 may extract, as extracted data from the information browsing ability data, the information browsing ability of the user corresponding to the behavioral conditions satisfied by the user's current behavior. Note that the information browsing ability of the user corresponding to the behavioral conditions satisfied by the user's current behavior may correspond to the information browsing ability of the user corresponding to a behavior history that matches or is similar to the user's current behavior.

[0092] The information browsing ability estimation unit 140 may then estimate the average value of the extracted data as the user's current information browsing ability. Note that the average value of the extracted data may correspond to an example of a representative value of the extracted data. Therefore, instead of the average value of the extracted data, other representative values of the extracted data (e.g., mode, median, etc.) may be used.

[0093] 5, the information browsing ability is expressed by any one of −1, 0, and +1. Therefore, the user's current information browsing ability estimated according to the example shown in FIG. 5 can be expressed by any one of −1 to +1. Information browsing ability estimation unit 140 outputs the user's current information browsing ability to information notification unit 160.

[0094] After the user's current information browsing ability is output to the information notification unit 160, the operation of the information notification system 1 proceeds to (S5) determining the level of the information browsing ability.

[0095] (S5) Determining the level of information browsing ability The information notification unit 160 determines whether the user's current information browsing ability output from the information browsing ability estimation unit 140 is greater than a predetermined value. Here, the predetermined value is also expressed as TH. The specific magnitude of the predetermined value is not limited. For example, the predetermined value may be 0.

[0096] If the user's current information browsing ability is greater than a predetermined value, the operation of the information notification system 1 shifts to (S6) information notification. If the user's current information browsing ability is equal to or less than a predetermined value, the operation of the information notification system 1 shifts to (S1) acquisition of browsing management data and behavior data.

[0097] (S6) Information notification The information notification unit 160 notifies the user terminal 20 of a message based on the fact that the user's current information browsing ability is greater than a predetermined value. The message notified by the information notification unit 160 is received by the user terminal 20. When the message is opened by the user terminal 20 based on the user's operation to open the message, opening response data is transmitted from the user terminal 20 to the information notification unit 160.

[0098] Fig. 6 is a diagram illustrating the operation of the information notification unit 160. As shown in Fig. 6, the user's current information browsing ability estimated in S4 can vary within a range from -1 to +1 depending on the user's situation.

[0099] 6, the timing of the information notification request calculated in S3 is indicated by a triangle. Referring to this timing of the information notification request, it can be seen that no information notification will be made even if an information notification request is output during a time period in which the estimated information browsing ability value is smaller than a predetermined value.

[0100] On the other hand, referring to Figure 6, the timing of information notification (i.e., the timing of message notification) is indicated by ▲. Referring to this timing of information notification, it can be seen that information notification (the message in the speech bubble shown in Figure 6) is performed during a time period when the information browsing ability estimate value is greater than a predetermined value.

[0101] [1-3. Explanation of effects] As described above, according to an embodiment of the present invention, an information browsing ability estimation device 10 is provided, which includes a browsing history output unit 120 that outputs browsing management data including one or more information browsing histories of a user, a behavioral history output unit 130 that outputs behavioral data including one or more behavioral histories of the user, and an information browsing ability estimation unit 140 that estimates the user's current information browsing ability based on the browsing management data, the behavioral data, and the user's current behavior.

[0102] With this configuration, the user's ability to view messages can be estimated with higher accuracy.

[0103] In addition, by notifying the user terminal 20 of a message based on the information viewing ability, the likelihood that the user will open and view the message can be increased. Furthermore, by notifying the user terminal 20 of a message based on the information viewing ability, the problem of notifications of unopened messages reducing user satisfaction or network utilization efficiency can be resolved.

[0104] The details of the embodiment of the present invention have been described above.

[0105] <2. Hardware configuration example> Next, an example of the hardware configuration of an information processing device as an example of the information browsing ability estimation device 10 according to an embodiment of the present invention will be described. Fig. 7 is a diagram showing the hardware configuration of an information processing device as an example of the information browsing ability estimation device 10 according to an embodiment of the present invention. The hardware configuration of the user terminal 20 may also be realized in the same manner as the hardware configuration of the information processing device 900 shown in Fig. 7.

[0106] As shown in FIG. 7, the information processing device 900 includes a CPU (Central Processing Unit) 901, a ROM (Read Only Memory) 902, a RAM (Random Access Memory) 903, a host bus 904, a bridge 905, an external bus 906, an interface 907, an input device 908, an output device 909, a storage device 910, and a communication device 911.

[0107] The CPU 901 functions as an arithmetic processing unit and control unit, and controls the overall operation of the information processing device 900 in accordance with various programs. The CPU 901 may also be a microprocessor. The ROM 902 stores programs used by the CPU 901, calculation parameters, etc. The RAM 903 temporarily stores programs used in the execution of the CPU 901, parameters that change as appropriate during the execution, etc. These are interconnected by a host bus 904 that is composed of a CPU bus, etc.

[0108] The host bus 904 is connected to an external bus 906, such as a PCI (Peripheral Component Interconnect / Interface) bus, via a bridge 905. It is not necessary to configure the host bus 904, bridge 905, and external bus 906 separately, and these functions may be implemented on a single bus.

[0109] The input device 908 is composed of input means for the user to input information, such as a mouse, keyboard, touch panel, buttons, microphone, switches, and levers, and an input control circuit that generates an input signal based on the user's input and outputs it to the CPU 901. By operating this input device 908, the user who operates the information processing device 900 can input various data to the information processing device 900 and instruct the information processing device 900 to perform processing operations.

[0110] The output device 909 includes, for example, a display device such as a CRT (Cathode Ray Tube) display device, a liquid crystal display (LCD) device, an OLED (Organic Light Emitting Diode) device, or a lamp, and an audio output device such as a speaker.

[0111] The storage device 910 is a device for storing data. The storage device 910 may include a storage medium, a recording device for recording data on the storage medium, a reading device for reading data from the storage medium, and a deletion device for deleting data recorded on the storage medium. The storage device 910 is configured, for example, with an HDD (Hard Disk Drive). This storage device 910 drives a hard disk and stores programs executed by the CPU 901 and various data.

[0112] The communication device 911 is, for example, a communication interface configured with a communication device for connecting to a network, etc. The communication device 911 may be compatible with either wireless communication or wired communication.

[0113] An example of the hardware configuration of the information processing device 900 according to an embodiment of the present invention has been described above.

[0114] <3. Modifications> Although the preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, the present invention is not limited to these examples. It is clear that a person skilled in the art to which the present invention pertains can conceive of various modifications and alterations within the scope of the technical ideas set forth in the claims, and it is understood that these also naturally fall within the technical scope of the present invention.

[0115] [3-1. User-related variations] For example, in the above description, the case where the user whose information browsing ability is calculated in S2 and registered in information browsing ability accumulation unit 150 (hereinafter also referred to as the "registered user") and the user whose information browsing ability is estimated in S4 (hereinafter also referred to as the "estimated user") are the same user has been mainly described. However, the registered user and the estimated user may be different users.

[0116] Furthermore, each of the registered user and the presumed user does not have to be a single user. That is, the registered user may include multiple users, and the presumed user may include multiple users. When the registered user includes multiple users, the multiple users may form a user group. Similarly, when the presumed user includes multiple users, the multiple users may form a user group. When the presumed user forms a user group, a message can be notified to the user group all at once.

[0117] The registered user and the presumed user may or may not have a common user. In either case, it is desirable that the registered user and the presumed user belong to the same group. Users belonging to the same group may be employees working at the same workplace or residents living in the same area.

[0118] Since users belonging to the same group are expected to be likely to take the same or similar actions, it is believed that the information browsing ability of the estimated target user can be estimated with higher accuracy based on the behavioral history of the registered target user. Furthermore, by notifying the estimated target user of a message based on their information browsing ability, the likelihood that the estimated target user will open and view the message can be increased.

[0119] [3-2. Adding a message ID] The above describes a case where a message ID is not attached to a message notified by the information notification unit 160. However, a message ID may be attached to a message notified by the information notification unit 160.

[0120] At this time, a message ID may be assigned to each of the notification time included in the information notification data and the opening time included in the opening response data. Then, the browsing history output unit 120 may generate browsing management data by associating the notification time and the opening time that are assigned the same message ID. This reduces the possibility of incorrectly associating the notification time and the opening time even when multiple messages are notified, so that the information browsing ability based on the notification time and the opening time can be estimated with higher accuracy.

[0121] [3-3. Variations related to acceptability] The above description mainly deals with the case where the information browsing ability estimation unit 140 calculates the information browsing ability based on the information browsing history included in the browsing management data. However, the information browsing ability estimation unit 140 may calculate the information browsing ability by taking into account not only the information browsing history but also other information.

[0122] The user may be able to input an acceptance level for a message when viewing the message. For example, the acceptance level may be a numerical value indicating the user's evaluation of the actual notification timing of the message. In this case, the user terminal 20 may accept the acceptance level (e.g., a three-level value) input by the user and associate the acceptance level with the opening time included in the opening response data transmitted from the user terminal 20 to the information notification unit 160.

[0123] That is, the opening time included in at least a part of the information browsing history may be associated with an acceptance level input by the user for the message. Then, the information browsing ability estimation unit 140 may calculate the information browsing ability of the user corresponding to the opening time associated with the acceptance level based on the acceptance level.

[0124] For example, the information viewing ability estimation unit 140 may correct the user's information viewing ability calculated based on the browsing history data as described above based on the acceptance level (for example, the higher the acceptance level, the higher the user's information viewing ability may be corrected).

[0125] This allows the user's evaluation of the timing of message notifications to be reflected in the information browsing ability, making it possible to estimate the information browsing ability with even greater accuracy. Furthermore, by notifying a user of a message based on their information browsing ability, the likelihood that the user will open and view the message can be further increased.

[0126] [3-4. Variations on system configuration] The above description has mainly focused on the case where the information notification system 1 includes an information browsing ability estimation device 10 equivalent to a single server and a user terminal 20 carried by a user. However, the physical configuration of the information notification system 1 is not limited. For example, the functions described as being possessed by a server may be installed in the user terminal 20. Furthermore, the user terminal 20 does not have to be a terminal carried by a user, but may be a terminal installed in a fixed location, or the user terminal 20 used by one user may be made up of multiple terminals.

[0127] [3-5. Modifications regarding behavior history and behavior conditions] The above description mainly deals with cases where the behavioral history includes all of the time, location, activity type, and weather. However, the behavioral history may include only some of the time, location, activity type, and weather. Furthermore, the above description mainly deals with an example where the time included in the behavioral condition is expressed using two values: a weekday / holiday classification and a time period. However, the time included in the behavioral condition may use the day of the week instead of the weekday / holiday classification. Furthermore, the season may be added to the time included in the behavioral condition.

[0128] [3-6. Variations on the value of information viewing ability] The above mainly describes an example in which the value of a user's information viewing ability included in the information viewing ability data is expressed as one of three values, -1, 0, or +1, based on the time of notification and the time of opening the message. However, the method of expressing a user's information viewing ability is not limited to this example. For example, the value of a user's information viewing ability may be expressed so that it peaks at the time of opening the message and decreases as the time moves away from that point.

[0129] [3-7. Variations on Estimation of Information Browsing Ability] The above description mainly focuses on an example in which the information browsing ability estimation unit 140 estimates the user's current information browsing ability based on the information browsing ability data and the user's current behavior. However, the method for estimating the user's current information browsing ability is not limited to this example. For example, a machine learning algorithm may be used to estimate the user's current information browsing ability.

[0130] For example, the information browsing ability estimation unit 140 may generate an inference model using a machine learning algorithm based on the user's information browsing ability and the behavioral data. More specifically, the information browsing ability estimation unit 140 may train the model using the user's information browsing ability as correct answer data and the behavioral data as training data.

[0131] The information browsing ability estimation unit 140 may then estimate the user's current information browsing ability based on the inference model and the user's current behavior. More specifically, the information browsing ability estimation unit 140 may use the user's current behavior as input data and estimate output data from the inference model as the user's current information browsing ability. Note that, while a neural network or the like may be used as the machine learning algorithm, the type of machine learning algorithm is not limited.

[0132] [3-8. Retention period of information accessibility data] In the above, no particular mention has been made about the retention period of information browsing ability data by information browsing ability accumulation unit 150. For example, the information browsing ability data retained by information browsing ability accumulation unit 150 may be all past data, or only data from a certain period of the past (e.g., three months).

[0133] [3-9. Modifications regarding acquisition of behavioral data] The above mainly describes an example in which the behavior history output unit 130 calculates the time, location, activity type, and weather using a beacon, GPS, walking, a built-in microphone, and an external weather service. However, the means and methods used to calculate the time, location, activity type, and weather are not limited to the examples described above. [Explanation of symbols]

[0134] 1. Information notification system 10 Information browsing ability estimation device 120 Browsing history output section 130 Action history output unit 140 Information Browsing Ability Estimation Department 150 Information Browsing Ability Storage Unit 160 Information Notification Department 20 User Devices

Claims

1. an estimation unit that estimates an information browsing ability of a second user based on browsing management data including one or more information browsing histories of a first user, behavior data including one or more behavior histories of the first user, and behavior of a second user; Each of the information viewing histories includes a viewing time, which is a time when the first notification information transmitted to the terminal of the first user is viewed by the first user, and a notification time, which is a time when the first notification information is transmitted to the terminal of the first user; The estimation unit Calculating the information browsing ability of the first user based on the browsing management data, and estimating the information browsing ability of the second user based on the information browsing ability of the first user, the behavior data, and the behavior of the second user; calculating the information browsing ability of the first user corresponding to a time later than the notification time and earlier than the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time; Information browsing ability estimation device.

2. the estimation unit calculates the information browsing ability of the first user corresponding to a time after the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time; The information browsing ability estimation device according to claim 1 .

3. The estimation unit calculates the information viewing ability of the first user corresponding to a time later than the notification time and earlier than the viewing time to be lower than the information viewing ability of the first user corresponding to a time later than the viewing time. The information browsing ability estimation device according to claim 2 .

4. the estimation unit generates information browsing ability data including one or more behavioral conditions according to the behavioral data and the information browsing ability of the first user corresponding to each of the behavioral conditions, and estimates the information browsing ability of the second user based on the information browsing ability data and the behavior of the second user. The information browsing ability estimation device according to any one of claims 1 to 3.

5. the estimation unit extracts, from the information browsing ability data, information browsing ability of the first user corresponding to a behavioral condition satisfied by the behavior of the second user as extracted data, and estimates an average value of the extracted data as the information browsing ability of the second user; The information browsing ability estimation device according to claim 4 .

6. the estimation unit generates an inference model using a machine learning algorithm based on the information browsing ability of the first user and the behavioral data, and estimates the information browsing ability of the second user based on the inference model and the behavior of the second user; The information browsing ability estimation device according to any one of claims 1 to 4.

7. a viewing time included in at least a part of the information viewing history is associated with an acceptance level input by the first user for the first notification information; the estimation unit calculates, based on the receptivity, the information browsing ability of the first user corresponding to the browsing time associated with the receptivity; The information browsing ability estimation device according to any one of claims 1 to 6.

8. The information browsing ability estimation device includes: an information notification unit that notifies a terminal of the second user of second notification information based on the information browsing ability of the second user being greater than a predetermined value; The information browsing ability estimation device according to any one of claims 1 to 7.

9. Each of the behavioral histories of the first user includes at least one of a location where the first user was present, a time when the first user was present, an activity type of the first user, and weather at a location where the first user was present; The information browsing ability estimation device according to any one of claims 1 to 8.

10. the first user includes one or more users; the second user includes one or more users; The first user and the second user have a common user. The information browsing ability estimation device according to any one of claims 1 to 9.

11. the first user includes one or more users; the second user includes one or more users; The first user and the second user do not have a common user. The information browsing ability estimation device according to any one of claims 1 to 9.

12. The first user and the second user belong to the same group. The information browsing ability estimation device according to any one of claims 1 to 11.

13. 1. A computer-implemented information browsing ability estimation method, comprising: estimating an information browsing ability of a second user based on browsing management data including one or more information browsing histories of a first user, behavioral data including one or more behavioral histories of the first user, and behavior of the second user, Each of the information viewing histories includes a viewing time, which is a time when the first notification information transmitted to the terminal of the first user is viewed by the first user, and a notification time, which is a time when the first notification information is transmitted to the terminal of the first user; The computer Calculating the information browsing ability of the first user based on the browsing management data, and estimating the information browsing ability of the second user based on the information browsing ability of the first user, the behavior data, and the behavior of the second user; calculating the information browsing ability of the first user corresponding to a time later than the notification time and earlier than the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time; A method for estimating information browsing ability.

14. Computer, an estimation unit that estimates an information browsing ability of a second user based on browsing management data including one or more information browsing histories of a first user, behavior data including one or more behavior histories of the first user, and behavior of a second user; Each of the information viewing histories includes a viewing time, which is a time when the first notification information transmitted to the terminal of the first user is viewed by the first user, and a notification time, which is a time when the first notification information is transmitted to the terminal of the first user; The estimation unit Calculating the information browsing ability of the first user based on the browsing management data, and estimating the information browsing ability of the second user based on the information browsing ability of the first user, the behavior data, and the behavior of the second user; calculating the information browsing ability of the first user corresponding to a time later than the notification time and earlier than the browsing time to be lower than the information browsing ability of the first user corresponding to the browsing time; A program that functions as an information browsing ability estimation device.

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