JP6389301B1 - Determination device, determination method, and determination program - Google Patents

Abstract

An object of the present invention is to accurately determine the possibility that a call with a user is established for a call.
A determination apparatus according to the present application includes an acquisition unit and a determination unit. The acquisition unit acquires the usage status of the terminal used by the user. The determination unit determines the possibility of a user's call at a predetermined timing based on the relationship between the usage status acquired by the acquisition unit and the possibility of a call that is a possibility that the user will make a call to the call. To do. For example, the acquisition unit acquires terminal position information as the usage status. The determination unit determines a user's call possibility based on the position information.
[Selection] Figure 1

Description

  The present invention relates to a determination device, a determination method, and a determination program.

  Some services provided to the user change the efficiency of the service depending on whether or not the user answers the phone. For example, in a service that requires the identity verification via a telephone call, the service cannot be provided unless the user answers the phone, which may cause inconvenience. In addition, even for services other than services, for example, for businesses that operate by telephone, priority is given to users who have a high possibility of establishing a call with the user for telephone calls (hereinafter referred to as “callability”). The more you call, the more efficient your business is.

  Here, as a technique for supporting a process of making a call (calling process), a technique for receiving request information indicating a request of a user who receives a call and performing call control based on the received information has been proposed. Yes.

Japanese Patent Laying-Open No. 2015-69535

  However, with the above-described conventional technology, it is difficult to accurately determine the possibility that a call with the user is established for a call. For example, in the above-described conventional technology, it is necessary to previously receive a request regarding a call timing from a user. For this reason, in the above-described conventional technology, for example, it is difficult to determine the possibility of a call with a user who has not received a request or to determine the possibility of a call according to a situation that changes in real time.

  The present application has been made in view of the above, and an object of the present invention is to provide a determination device, a determination method, and a determination program capable of accurately determining the possibility that a call with a user is established for a call. And

  The determination apparatus according to the present application includes an acquisition unit that acquires a usage status of a terminal used by a user, a usage status acquired by the acquisition unit, and a call possibility that a user may make a call with respect to a call And a determination unit that determines a call possibility of the user at a predetermined timing based on the relationship with

  According to one aspect of the embodiment, there is an effect that it is possible to accurately determine a user's call possibility.

FIG. 1 is a diagram illustrating an example of a determination process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of a determination processing system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the determination apparatus according to the embodiment. FIG. 4 is a diagram illustrating an example of an attribute table according to the embodiment. FIG. 5 is a diagram illustrating an example of a sensor table according to the embodiment. FIG. 6 is a diagram illustrating an example of a service table according to the embodiment. FIG. 7 is a diagram illustrating an example of the definition table according to the embodiment. FIG. 8 is a diagram illustrating an example of a learning data table according to the embodiment. FIG. 9 is a diagram illustrating an example of a model table according to the embodiment. FIG. 10 is a diagram illustrating an example of a call state storage unit according to the embodiment. FIG. 11 is a diagram illustrating a configuration example of a user terminal according to the embodiment. FIG. 12 is a flowchart (1) illustrating a processing procedure according to the embodiment. FIG. 13 is a flowchart (2) illustrating a processing procedure according to the embodiment. FIG. 14 is a flowchart (3) illustrating a processing procedure according to the embodiment. FIG. 15 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the determination apparatus.

  Hereinafter, modes for carrying out a determination apparatus, a determination method, and a determination program according to the present application (hereinafter referred to as “embodiments”) will be described in detail with reference to the drawings. Note that the determination device, the determination method, and the determination program according to the present application are not limited by this embodiment. In addition, the embodiments can be appropriately combined within a range that does not contradict processing contents. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description is omitted.

[1. Example of judgment process)
First, an example of the determination process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a determination process according to the embodiment. In FIG. 1, the determination device 100 according to the present application determines a predetermined timing based on a relationship between a usage status of a terminal owned by the user and a call possibility that is a possibility that the user can make a call with respect to a call. The example in which the process which determines the telephone call possibility of the said user in is performed is shown.

  The determination apparatus 100 shown in FIG. 1 acquires the usage status of a terminal used by the user (the user terminal 10 in the example of FIG. 1), and based on the relationship between the acquired usage status and the user's call possibility. A server device that performs a process of determining a user's call possibility at a predetermined timing.

  A user terminal 10 illustrated in FIG. 1 is an information processing terminal such as a smartphone used by a user. A user U01 shown in FIG. 1 is an example of a person to be called for a person who calls a customer (hereinafter referred to as “caller”). In the example illustrated in FIG. 1, the user terminal 10 is used by the user U01. Although illustration in FIG. 1 is omitted, the number of user terminals 10 according to the embodiment is not limited to one, and a plurality of user terminals 10 may exist. That is, the user U01 may have a plurality of user terminals 10. Hereinafter, the user may be read as the user terminal 10. For example, the description “user U01 accesses determination device 100” may actually indicate a situation where “user terminal 10 used by user U01 accesses determination device 100”.

  In the embodiment, the usage status of the user terminal 10 is provided to the user via, for example, sensing information detected (sensing) by the user terminal 10, information on a user operation on the user terminal 10, or a network. Includes service usage history.

  The services provided to the user via the network are, for example, various web services provided via a network such as the Internet. In the embodiment, the service is provided by a service server 30 (not shown in FIG. 1) such as a web server. As an example, when the service server 30 receives a login from a user, the service server 30 provides a portal service that provides a portal site customized for the user. The service server 30 registers a search service, a shopping service, an auction service, an information providing service (for example, a map information service, a navigation service, a news service, a weather forecast service), a task setting, and a schedule. Various services such as a calendar service may be provided. Note that the service server 30 according to the embodiment is not limited to one, and a plurality of service servers 30 may be provided, each providing a different service. Further, the usage status of the user terminal 10 includes information transmitted / received by the user U01 when using the service and information regarding the context of the user U01 when using the service. In addition, the usage status in the service may include attribute information registered for the user U01 service when using the service (for example, the age and sex of the user U01, the place of residence, the occupation, and the workplace). .

  The caller apparatus 50 shown in FIG. 1 is an information processing apparatus used by a business operator who makes a call to a user. For example, the caller apparatus 50 acquires information on the call possibility of each user who is a customer from the determination apparatus 100, and performs call control based on the acquired call possibility. Specifically, the call carrier apparatus 50 performs call control so that a call with a high call possibility is preferentially called. It should be noted that the caller may include various business operators such as a business operator who conducts business by telephone, a business operator who performs a reminder, and a business operator who performs identity verification by telephone. In the embodiment, an example in which the caller makes a call to the user terminal 10 having the mobile phone function is shown. You may call the office.

  In the example illustrated in FIG. 1, the determination device 100 determines the possibility of a call of the user U01 and transmits the determined result to the caller. That is, when the caller tries to call the user U01, the determination apparatus 100 notifies in advance of the possibility of indicating whether or not the user U01 will answer the call, or has a possibility of calling more than the user U01. Notify other high user information. Thereby, the determination apparatus 100 enables a smooth call process. Hereinafter, the flow of the determination process according to the embodiment by the determination apparatus 100 will be described with reference to FIG.

  In the example of FIG. 1, the user U01 carries the user terminal 10 and uses the user terminal 10 in various situations. For example, the user U01 operates the user terminal 10 while walking or browses the screen of the user terminal 10 in a commuter train. Even if the user terminal 10 is not operated by the user U01, the user terminal 10 obtains various information such as position information, acceleration information, and tilt information by being carried by the user U01 when moving from home or office. That is, the user terminal 10 obtains the usage status in the user terminal 10 by being used from the user U01 on a daily basis (step S11).

  For example, the determination apparatus 100 requests the user terminal 10 to transmit the usage status. And the determination apparatus 100 acquires the utilization condition of the user terminal 10 from the user terminal 10 which responded to a request | requirement (step S12). The determination apparatus 100 stores the acquired usage status in the usage status storage unit 121. Note that the determination apparatus 100 may acquire the usage status of the user terminal 10 via the service server 30 accessed by the user terminal 10 to use the service.

  The determination apparatus 100 acquires all usage situations used to determine the call possibility of the user U01.

  For example, the determination apparatus 100 acquires the position information of the user terminal 10 as the usage status. This is because the possibility of a call is relatively high when the user U01 is located at home, and when the user U01 is located at the office during work hours or while traveling by train or airplane, This is because it is estimated that the call possibility is relatively low, and thus the position information can be a determination element for the call possibility.

  Specifically, the determination apparatus 100 acquires position information acquired by a GPS (Global Positioning System) function of the user terminal 10 every predetermined time (for example, every minute). The position information acquired by the determination apparatus 100 is not limited to the position information acquired by the GPS function, and may be position information estimated from the IP address of the user terminal 10 that has accessed any information device, for example. Good. Further, the position information may be a specific numerical value indicating longitude or latitude, or address information indicating a predetermined area. In this case, for example, the determination apparatus 100 refers to a definition database or the like for associating position information and address information, and specifies address information from the acquired position information.

  In the embodiment, the determination apparatus 100 may specify the position of the user U01 such as the home or work place by various methods. For example, the determination apparatus 100 may identify the address and work place of the user U01 based on user information registered by the user U01 in a predetermined service (for example, information presented to the service side in member registration for the service). Good. Alternatively, the determination apparatus 100 estimates the position indicated by the position information frequently observed early in the morning or at night in the position information continuously acquired from the user terminal 10, and specifies the position of the user U01's home. Also good. Further, the determination apparatus 100 may estimate the position indicated by the position information frequently observed during the weekday daytime as the work place, and specify the position of the work place of the user U01.

  Further, the determination apparatus 100 may acquire operation information indicating the physical operation of the user U01 with respect to the user terminal 10. Specifically, the determination apparatus 100 acquires acceleration information detected by the user terminal 10, inclination information, pressure information for the user terminal 10, and the like. Then, for example, the determination apparatus 100 acquires a usage situation that the user terminal 10 is touching the hand of the user U01 or that the user U01 is browsing the screen with the user terminal 10 with one hand.

  Further, the determination apparatus 100 may acquire operation information indicating whether or not the user U01 is operating the user terminal 10. Specifically, the determination apparatus 100 activates that the user U01 is operating the touch panel of the user terminal 10 or an arbitrary application program (hereinafter referred to as “app”) installed in the user terminal 10. Use status such as being active or operating an application.

  Further, the determination apparatus 100 may acquire environment information around the user terminal 10. For example, the determination apparatus 100 acquires illuminance information acquired by an illuminance sensor included in the user terminal 10. Specifically, the determination apparatus 100 acquires a usage status such as whether the user terminal 10 is placed in the open air or placed in the user's bag or pocket based on the illuminance information.

  Further, the determination apparatus 100 may acquire connection information indicating whether or not the user terminal 10 is playing music and an audio output device (for example, an earphone) is connected to the user terminal 10.

  For example, when a usage situation such as the user U01 holding the user terminal 10, listening to music, or not being stored in a bag is acquired, the user U01 receives a call. It is estimated that there is a high possibility that a telephone call can be made compared to a case where the user terminal 10 is not at hand. As described above, the determination apparatus 100 acquires the various usage situations detected by the user terminal 10 to determine whether or not the user U01 can easily receive a call, and determines whether or not the user U01 can make a call. judge.

  Note that the determination apparatus 100 may acquire a usage status regarding a service used via the user terminal 10 as the usage status of the user terminal 10. Specifically, the determination apparatus 100 acquires schedule information on which the user U01 has made a reservation in a reservation service such as a restaurant, a transportation facility, or an accommodation facility. In addition, the determination apparatus 100 acquires schedule information specifying that the user U01 has purchased a product in the shopping service and the delivery date and time of the product as the usage status.

  For example, during the time period when the user U01 reserves transportation, etc., there is a high possibility that the user U01 is using some kind of transportation, so the possibility that the user U01 makes a call to the call is relatively low. It is estimated to be. Also, during the time period in which the user U01 designates the delivery date and time of the product, for example, the user U01 is at home to wait for the delivery company to arrive or waits for a call from the delivery company. It is estimated that the possibility of performing is relatively high.

  Furthermore, the determination apparatus 100 may acquire the communication status of the user terminal 10 when using the service as the usage status. For example, the determination apparatus 100 acquires a situation in which the user terminal 10 performs short-range communication such as Bluetooth (registered trademark) with an IoT (Internet of Things) device installed in the home of the user U01. In this case, it can be said that the user U01 has a relatively high possibility of a call. Then, at the timing of being at home, it is estimated that the user U01 is more likely to receive a call than when he is out. Thus, the determination apparatus 100 acquires various usage situations used for determining the possibility of a call.

  Further, the determination apparatus 100 may continuously acquire the usage status of the user terminal 10 over a predetermined period (for example, one month or one year) in association with each day of the week or time period. The determination apparatus 100 can accumulate the usage status of the user terminal 10 in association with each day of the week or time period by continuously acquiring the usage status.

  Then, the determination apparatus 100 determines the call possibility of the user U01 based on the acquired usage situation (step S13). For example, the determination apparatus 100 holds a database (denoted as “definition file” in the example of FIG. 1) in which a definition for defining the relationship between the acquired usage situation and the call possibility of the user U01 is described. To do. The contents of the definition file are set by, for example, the administrator of the determination apparatus 100.

  In the definition file, the relationship between the usage status of the user terminal 10 and the call possibility is defined. Specifically, the definition file defines an index value (score) such as how much a call is likely to occur when a specific usage situation is observed at the user terminal 10 at the time to be determined. It is done. For example, in the example of FIG. 1, it is assumed that the definition file indicates the possibility of a user's call when a certain usage situation is observed as a score from “−100” to “100”. In this example, it is shown that the higher the score, the higher the possibility that the user U01 can talk. In addition, when a plurality of usage situations are observed at a predetermined timing (hereinafter, sometimes referred to as “target date and time”) as a determination target, the determination apparatus 100 adds such scores, Assume that the possibility of a call of a user to be determined is determined. Although details will be described later, the score is not necessarily fixed, and may change dynamically by learning, for example. Moreover, a score is not common with respect to all the users, and may change dynamically for every user. The score only indicates the relative possibility of a call, and the numerical value itself may not have an absolute meaning.

  As an example, in the definition file, the position information acquired from the user terminal 10 at the target date and time matches the position information indicating the position of the user U01's home, or within a predetermined range (for example, a range within several meters from the home) Etc.), the definition that the score indicating the call possibility of the user U01 is “40” is described. This is because it is estimated that when the user U01 is at home at the target date and time, the possibility that the user U01 makes a call to the call is relatively higher than when the user U01 is out or at work Is shown.

  In the definition file, when there is a difference between the determination timing and the actual call timing, a score regarding the usage situation estimated at the actual call timing may be described. For example, in the definition file, position information acquired from the user terminal 10 a predetermined time before the target date and time is within a predetermined range from the position of the user U01's home (for example, the user U01 can return home after the predetermined time) In such a case, the definition that the score indicating the call possibility of the user U01 is “20” may be described. This is because the user U01 is not at home at the target date and time, but there is a possibility that the user U01 is at home at the timing of actually making a call. Show. Note that these scores may vary depending on the position where the user U01 is located. For example, it is assumed that the position information acquired from the user terminal 10 a predetermined time before the target date and time is position information that indicates a position far away from the home position of the user U01 (for example, an overseas country). In this case, since the possibility that the user U01 makes a call to the call at the target date and time is extremely low, the score corresponding to the situation may be defined as “−100” in the definition file.

  As another example, in the definition file, when the user U01 registers schedule information such as a restaurant or accommodation facility reservation at the target date and time, a score indicating the call possibility of the user U01 at the target date and time A definition such as “−10” may be described. This is because if the target date and time overlaps with the time when the user U01 reserved a restaurant or the like, it is estimated that the possibility that the user U01 will respond to the call is relatively low at the target date and time. It is.

  As another example, when the user U01 designates delivery of a product purchased using a shopping service at the target date and time in the definition file, the score indicating the call possibility of the user U01 at the target date and time is “ The definition of “30” is described. If the target date and time overlaps with the time when the user U01 designates delivery, the user U01 is at home at the target date and time, and the possibility of responding to the call is relatively high. It is estimated. Thus, the determination apparatus 100 holds a plurality of definitions indicating the relationship between the usage status of the user terminal 10 and the call possibility of the user U01.

  Then, the determination apparatus 100 determines the call possibility of the user U01 at the time to be determined based on these definition files. For example, the determination apparatus 100 determines the call possibility of the user U01 using the time specified by the caller as the target date and time.

  For example, it is assumed that the determination apparatus 100 is requested by the caller to determine the call possibility of the user U01 “10 minutes after the current time”. In this case, the determination apparatus 100 extracts a usage situation that is related to the possibility of a call from the usage situation in the service of the user U01, and calculates a score corresponding to the extracted usage situation. The possibility of telephone conversation of the user U01 later is determined.

  For example, it is assumed that the position information of the user U01 at the present time indicates the vicinity of the user U01's home or a position where the user U01 is estimated to be able to return home within 10 minutes. In this case, the determination apparatus 100 adds “40” or “20”, which is the above-described score, to the score indicating the call possibility of the user U01. Further, it is assumed that the user U01 has designated delivery of a product purchased using a shopping service at the target date and time (that is, 10 minutes after the current time). In this case, the determination apparatus 100 adds “30”, which is the above-described score, to the score indicating the call possibility of the user U01. Then, it is assumed that the usage situation in the service of the user U01 and used for measuring the call possibility of the user U01 has not been extracted other than the above. In this case, the determination apparatus 100 determines that the score indicating the call possibility of the user U01 two hours after the current time is “70” or “50”.

  Then, the determination device 100 transmits the call possibility of the user U01 determined based on the calculated score to the caller (step S14). For example, the determination apparatus 100 normalizes the calculated score and transmits the call possibility expressed as a percentage to the caller apparatus 50 used by the caller.

  The caller makes a call to the user U01 based on the call possibility transmitted from the determination apparatus 100 (step S15). For example, when the caller receives a determination result that the user U01 has a relatively high possibility of calling from the determination apparatus 100, the caller actually calls the user U01 and provides a predetermined service. Alternatively, when the caller receives a determination result that the user U01 has a relatively low possibility of calling from the determination apparatus 100, the caller may take a response to call the user U01 at another date and time instead of the target date and time. Or, instead of the user U01, the caller may take a response to call another customer who has a higher call possibility than the user U01.

  Note that the determination apparatus 100 may not only determine the possibility of a call based on a predetermined determination element, but also perform a predetermined learning process to improve the determination accuracy.

  For example, in step S15, when the caller actually calls the user U01, the caller can acquire the result information indicating whether or not the user U01 responded to the call. In other words, the caller obtains result information indicating whether or not the result determined by the determination device 100 is correct.

  In this case, the caller transmits, for example, result information indicating whether or not the user U01 has responded to the call via the caller device 50 to the determination device 100 (step S16).

  Based on the result information transmitted from the caller, the determination device 100 learns the correlation between the usage status used for determining the call possibility of the user U01 and the result information. Then, the determination apparatus 100 reflects the learning and generates a calculation formula (model) for determining the call possibility of the user U01 (step S17). As will be described in detail later, as an example, the determination apparatus 100 uses learning result information as to whether or not the user U01 has responded to the call as an objective variable, and learns by a regression analysis method using each usage situation used in the determination as an explanatory variable. I do. Thereby, the determination apparatus 100 can derive information such as what explanatory variable (usage status) contributes in determining the call possibility of the user U01. The determination apparatus 100 stores the generated model in the model storage unit 125.

  The determination apparatus 100 generates the above model for each user. If the user U01 tends to not respond to the call even if the user U01 is at home, the usage situation that the user U01 is at home can be said to have a low rate of contribution to the call possibility determination. Moreover, even if the user U01 registers a schedule in the service, if the tendency to act according to the schedule is weak, it can be said that the registered schedule information has a low rate of contribution to the call possibility determination. On the other hand, if the user U01 has a tendency to respond to the call even if he / she is on duty, the usage status that the user U01 is busy is determined as a negative example (call) It can be said that it contributes to the positive side (responds to the call), not to Thus, the relationship between the call possibility and the usage situation may contribute to different results for each user. For this reason, the determination apparatus 100 generates a model for each user so that the possibility of a call can be derived based on the characteristics of the individual behavior. In this case, the determination apparatus 100 may update the model stored in the model storage unit 125 every time the result information is acquired.

  Specifically, the determination apparatus 100 may update a definition file applied to each user as the learning progresses. For example, as described above, for a user who has a strong tendency that the position information acquired from the user terminal 10 does not contribute to the call possibility determination, the determination apparatus 100 determines the score corresponding to the position information according to the learning result. However, a weight that is calculated to be lower than other users may be given. Or about the user who always tends to respond to a call at the designated delivery date and time, the determination device 100 calculates a score corresponding to the usage status higher than that of other users. A weight may be added. In other words, the determination apparatus 100 can generate a model for each user using a score with a weight corresponding to each user to obtain a call possibility.

  Moreover, the determination apparatus 100 may perform determination in consideration of a day of the week or a time zone. Even if the usage status corresponding to the target date and time cannot be acquired from the user U01, the determination apparatus 100 determines the possibility of a call on the same day in the past or the same time period in the past, and acquires the result information. There is a possibility. In this case, for example, the determination apparatus 100 may determine the call possibility of the user U01 at the target date and time by reflecting the call possibility of the user U01 in the same past day of the week or the same past time zone. Specifically, when the user U01 has been at home on the same day of the week or at the same time in the past, the determination apparatus 100 performs adjustment such as calculating the call possibility relatively high at the current target date and time. May be.

  As described above with reference to FIG. 1, the determination apparatus 100 according to the embodiment acquires the usage status of the terminal used by the user U01, and the user makes a call to the acquired usage status and the call. Based on the relationship with the call possibility, which is a possibility to be performed, the call possibility of the user U01 at a predetermined timing is determined.

  As described above, the determination apparatus 100 makes a request regarding the call timing to the caller or registers the call timing in order to determine the call possibility of the user U01 based on the usage situation in the user terminal 10. Even without this, it is possible to determine the call possibility of the user U01 based on the daily situation of the user U01. In addition, since the determination apparatus 100 performs determination based on the usage situation, for example, it is possible to make a call by determining real-time information such as the user U01 holding the user terminal 10 or operating an application. Gender can be determined. Furthermore, the determination apparatus 100 can also perform determination in consideration of the usage status of services used via the user terminal 10. In other words, the determination apparatus 100 is in a situation where the user U01 is in the timing of making a call such as the user U01 being registered in the schedule service or having specified the delivery date and time in the shopping service. , And the possibility of a call can be determined. Thereby, the determination apparatus 100 can accurately determine the possibility that a call with the user U01 is established for the call. Hereinafter, the configuration of the determination apparatus 100 that performs such processing and the determination processing system 1 including the determination apparatus 100 will be described in detail.

[2. Judgment processing system configuration]
The configuration of the determination processing system 1 including the determination device 100 according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the determination processing system 1 according to the embodiment. As illustrated in FIG. 2, the determination processing system 1 according to the embodiment includes a user terminal 10, a service server 30, a caller apparatus 50, and a determination apparatus 100. These various devices are communicably connected via a network N by wire or wireless. Note that the determination processing system 1 illustrated in FIG. 2 may include a plurality of user terminals 10, a plurality of service servers 30, and a plurality of caller apparatuses 50.

  The user terminal 10 is, for example, an information processing apparatus such as a smartphone, a desktop PC (Personal Computer), a notebook PC, a tablet terminal, a mobile phone, a PDA (Personal Digital Assistant), or a wearable device. It is. Furthermore, the user terminal 10 may include various smart devices having an information processing function. For example, the user terminal 10 may include a smart home appliance such as a TV (television) or a stationary speaker, a smart vehicle such as an automobile, a drone, a home robot, and the like.

  For example, the user terminal 10 acquires a web page from a website provided from the service server 30 by accessing the service server 30 in accordance with an operation by the user. Then, the user terminal 10 displays the acquired web page on a display device (for example, a liquid crystal display). Further, when the user uses a service, the user terminal 10 may detect information regarding the service and transmit the detected information to the service side. For example, the user terminal 10 may transmit the detected position information to the service server 30 at a timing when the user uses a predetermined service.

  The service server 30 is a server device that provides various services when accessed from the user terminal 10. The service server 30 is, for example, a portal site, news site, weather forecast site, shopping site, auction site, finance (stock price) site, route search site, map providing site, travel information site, restaurant introduction site, restaurant, etc. Various services are provided through various web pages related to reservation sites, web blogs, SNS (Social Networking Service), and the like.

  In addition, the service server 30 may acquire the usage status of the user terminal 10 in the service. For example, when the service server 30 provides a service related to a portal site, the service server 30 acquires user registration information (attribute information such as gender and age), location information at the time of login, and the like as the usage status. To do. Further, when the service server 30 provides a service relating to purchase such as a shopping site or an auction site, the service server 30 uses the usage status as the frequency or purchase price at which the user purchases the product, or the delivery of the product. Get information such as the date and time to be specified. Further, the service server 30 acquires various usage statuses of the service every time the user uses the service in services other than the above. In addition, the service server 30 may transmit the usage status of the user terminal 10 in the service to the determination apparatus 100.

  The caller apparatus 50 is an information processing apparatus used by the caller. The caller apparatus 50 may be a terminal used by each worker of the caller, or may be a server installed on the caller side. The caller apparatus 50 is not configured as a single apparatus, but may be a combination of a server and a terminal.

  For example, the caller apparatus 50 receives the call possibility for each user transmitted from the determination apparatus 100. Further, the caller apparatus 50 may transmit result information indicating whether or not the user has actually responded to the call to the determination apparatus 100 in accordance with an operation by the caller.

  The determination apparatus 100 acquires the usage status of the user terminal 10 used by the user, and based on the relationship between the acquired usage status and the call possibility that the user may make a call to the call, This is a server device that determines the possibility of a call of the user U01 at a predetermined timing. Note that the determination apparatus 100 may also function as the service server 30 that provides a service to the user.

[3. (Configuration of judgment device)
Next, the configuration of the determination apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the determination apparatus 100 according to the embodiment. As illustrated in FIG. 3, the determination apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The determination device 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator who uses the determination device 100, and a display unit (for example, a liquid crystal display) that displays various types of information. You may have.

(About the communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to the network N in a wired or wireless manner, and transmits / receives information to / from the user terminal 10, the service server 30, and the caller apparatus 50 via the network N.

(About the storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 includes a usage status storage unit 121, a model storage unit 125, and a call state storage unit 129.

(About usage status storage unit 121)
The usage status storage unit 121 stores information regarding the usage status of the user terminal 10. As shown in FIG. 3, the usage status storage unit 121 includes an attribute table 122, a sensor table 123A, a service table 123B, and a definition table 124 as data tables for storing information.

(About attribute table 122)
The attribute table 122 stores user attribute information. FIG. 4 shows an example of the attribute table 122 according to the embodiment. FIG. 4 is a diagram illustrating an example of the attribute table 122 according to the embodiment. In the example illustrated in FIG. 4, the attribute table 122 includes “user ID”, “owned terminal ID”, “phone number”, “phone type”, “gender”, “age”, “home position”, “job type”. And “working hours”.

  “User ID” is identification information for identifying a user. The “owned terminal ID” is identification information for identifying the user terminal 10 used by the user. The owned terminal ID is acquired, for example, when the service server 30 or the like recognizes unique identification information (device ID or the like) of the user terminal 10 when accessing the service using the user terminal 10. . Alternatively, the owned terminal ID may be acquired on the service side by a user using the service registering on the service side.

  Note that the information registered as the owned terminal ID may include the type of terminal. Specifically, in the information registered as the owned terminal ID, the terminal is a terminal (smart phone or wearable device) carried by the user, or a terminal that is generally not carried (installed at home). Such as a speaker or an IoT device such as a speaker or a desktop personal computer). Also, the information registered as the owned terminal ID has a response function to the call (for example, having identification information for responding to call control such as a telephone number and having a call function) Information such as whether or not it may be included. In the present specification, identification information as shown in FIG. 4 may be used as a reference symbol. For example, the user identified by the user ID “U01” may be referred to as “user U01”.

  “Telephone number” indicates the telephone number of the user. “Telephone type” indicates a type such as whether the registered telephone number is a mobile phone, a fixed phone, or a work phone. Note that only one telephone number is registered for each user, and a plurality of telephone numbers may be registered.

  “Gender” indicates the gender of the user who uses the service. “Age” indicates the age of the user. “Home position” indicates the position where the user's home is located. The “home position” may store not the specific address but position information (for example, longitude and latitude) corresponding to the user's home. “Job title” indicates the job title of the user. “Working time” indicates the working time of the user. The job type and working time may be information acquired by the service by the user registering with the service, or may be information estimated based on the usage status of the user terminal 10. For example, the determination apparatus 100 identifies the position of the work place of the user U01 based on the position information frequently observed during the weekday day among the position information transmitted from the user terminal 10. Furthermore, the determination apparatus 100 specifies a company name located at the position, a job type to which the company belongs, based on map information and the like held by the service. Then, the determination apparatus 100 stores the identified information in the attribute table 122 in association with the user.

  That is, the example of the data shown in FIG. 4 is attribute information related to the user U01 identified by the user ID “U01”, and the user terminal 10 used by the user U01 has the owned terminal ID “A01” or “A02”. Indicates that it will be identified. Further, the registered user U01 has a telephone number “XXXX”, and the telephone type corresponding to the telephone number is “mobile phone”. The sex of the user U01 is “male”, the age is “30s”, the address is “A prefecture...”, The occupation is “company employee (day shift)”, and the working hours are It is “9 o'clock to 17 o'clock”.

  The attribute information stored in the attribute table 122 is not necessarily accurate information. For example, the determination apparatus 100 may store “estimated sex”, “estimated age”, and the like estimated from the usage status of the user terminal 10 in the attribute table 122.

(About sensor table 123A)
Next, FIG. 5 shows an example of the sensor table 123A according to the embodiment. FIG. 5 is a diagram illustrating an example of the sensor table 123A according to the embodiment. The sensor table 123 </ b> A stores sensing information that is information detected by the user terminal 10 in the usage status of the user terminal 10. In the example illustrated in FIG. 5, the sensor table 123 </ b> A includes items such as “user ID”, “sensor log ID”, “acquisition date / time”, “sensing information”, and “acquisition content”.

  The “user ID” corresponds to the same item shown in FIG. “Sensor log ID” indicates identification information for identifying detected sensing information. “Acquisition date” indicates the date when the sensor log was acquired. Note that the determination apparatus 100 may acquire sensing information at regular intervals (for example, every minute or every 10 minutes), when a user uses a service, when a predetermined application is activated, Alternatively, it may be acquired at a timing when a specific context is observed (such as a timing when the user U01 visits his home or company).

  “Sensing information” indicates the type of information detected by the user terminal 10. “Acquired content” indicates the specific content of the acquired sensing information. In the example shown in FIG. 5, the acquired content is indicated by a conceptual notation such as “SE01”, but actually, when the sensing information is position information, specific latitude and longitude are indicated. Position information, information indicating an address and a region are stored.

  Further, if the sensing information is physical / acceleration information, the acquired content stores inclination information of the user terminal 10, specific numerical values of the acceleration information, and the like. In addition, as physical / acceleration information, not only specific numerical values but also the usage status of the user terminal 10 estimated from the numerical values may be stored. Specifically, the physical / acceleration information stores information indicating a situation such as “the user is touching the user terminal 10” or “the user is holding the user terminal 10”. May be.

  If the sensing information is an application operation, the number of applications activated by the user, the name of the application, the category of the application, and the like may be stored in the acquired content. The application operation may store operation information for operating the user terminal 10 in order for the user to operate the application.

  Further, if the sensing information is illuminance information, a specific numerical value of illuminance is stored in the acquired content. In addition, although illustration is abbreviate | omitted in FIG. 5, the information which the user terminal 10 detects is not restricted to illumination intensity but may be temperature and humidity.

  That is, the example of the data illustrated in FIG. 5 indicates that the sensor log B01 identified by the sensor log ID “B01” is stored as a log of information detected by the user terminal 10. Further, the sensor log B01 indicates that the acquisition date is “April 25, 2017 12:00”, the sensing information is “position information”, and the acquisition content is “SE01”.

(About service table 123B)
Next, FIG. 6 shows an example of the service table 123B according to the embodiment. FIG. 6 is a diagram illustrating an example of the service table 123B according to the embodiment. The service table 123B stores the usage status of the user terminal 10 in the service. In the example illustrated in FIG. 6, the service table 123B includes items such as “user ID”, “service use log ID”, “acquisition date / time”, “service”, “information type”, “acquisition information”, and “day information”. Have

  The “user ID” corresponds to the same item shown in FIG. “Service usage log ID” indicates identification information for identifying an action history (log) in which a user has used a service. “Acquisition date” indicates the date and time when the user's usage log was acquired. For example, the acquisition date and time is the date and time when the user logged into the service, the date and time when the user registered the schedule with the service, the date and time when the reservation to the restaurant was registered, or the like. For this reason, the acquisition date / time may not be related to the date / time for which the possibility of calling is determined. For example, in the case of schedule information, not the timing at which the schedule is registered, but the schedule registered as the schedule has a relationship with the date and time that is the subject of call possibility determination.

  “Service” indicates the type of service used by the user. “Information type” indicates the type of information acquired as the usage status. “Acquired information” indicates specific contents of the acquired usage status. That is, the acquired information may include information indicating a relationship with a date and time that is a determination target of call possibility when determining call possibility of the user. For example, in the case of schedule information, the schedule registered as a schedule has a relationship with the date and time for which the possibility of calling is determined. In the example shown in FIG. 6, a part of the acquired information is indicated by a conceptual notation such as “C01”. However, in actuality, when the acquired information is position information, a specific latitude or Location information indicating longitude and information indicating address and area are stored. “Day of the week information” indicates a day of the week that has a relationship with the date and time that is the subject of call possibility determination.

  That is, the example of the data illustrated in FIG. 6 indicates that the service usage log SB01 identified by the service usage log ID “SB01” is stored as a log in the service of the user U01. Further, the service use log SB01 has an acquisition date and time of “April 20, 2017 15:00”, is a log in a service related to “map / traffic”, and the information type acquired as the usage status is “location information”. This indicates that the acquired information is “C01”. Further, the information acquired as the service usage log SB01 indicates that the day of the week for which call possibility is determined is a “Thursday”.

(About the definition table 124)
Next, FIG. 7 shows an example of the definition table 124 according to the embodiment. FIG. 7 is a diagram illustrating an example of the definition table 124 according to the embodiment. The definition table 124 stores information defining the relationship between call possibility and usage status. For example, the information stored in the definition table 124 corresponds to the information described in the definition file shown in the description of FIG. In the example illustrated in FIG. 7, the definition table 124 includes items such as “definition ID”, “determination element”, “usage status”, and “score”.

  “Definition ID” indicates identification information for identifying each definition. The “determination element” indicates the type of usage status used as the determination element. “Usage status” indicates specific contents of usage status. “Score” indicates a numerical value to be added as a score indicating a user's call possibility when a defined usage situation is acquired at the date and time of determination.

  That is, in the example of the data illustrated in FIG. 7, the definition K01 identified by the definition ID “K01” relates to the sensing element “sensing”, and “has the terminal in hand” at the target date and time. When the usage status is acquired, “60” is added as a score indicating the call possibility of the user.

  As another example, the definition K11 is related to the determination element “service”, and when the usage status “at home” is acquired based on location information, for example, at the target date and time, It shows that “40” is added as a score indicating the possibility of the user's call. The location information may be acquired by a service such as a map information service or a navigation application, or may be acquired by sensing of the user terminal 10.

  As another example, the definition K21 is a score indicating the call possibility of the user if the determination element is related to “setting / history” and “the call target is a mobile terminal”. “10” is added. Further, the definition K22 relates to “setting / history” as a determination element, and “−10” as a score indicating the possibility of the user's call if the call target is a fixed phone. Is added. This generally indicates that a mobile phone is easier for a user to answer a phone call than a fixed phone. As will be described later, the score defined in the definition table 124 may change through a learning process performed by the determination apparatus 100.

(About the model storage unit 125)
The model storage unit 125 stores learning related to the relationship between the usage status and the possibility of calling and information related to the model generated as a result of the learning. As illustrated in FIG. 3, the model storage unit 125 includes a learning data table 126 and a model table 127 as data tables for storing information.

(About the learning data table 126)
The learning data table 126 stores information related to learning for generating a model for determining call possibility. FIG. 8 shows an example of the learning data table 126 according to the embodiment. FIG. 8 is a diagram illustrating an example of the learning data table 126 according to the embodiment. In the example illustrated in FIG. 8, the learning data table 126 includes “learning data ID”, “user ID”, “target date / time”, “target day of the week”, “call result information (objective variable)”, “usage status data”. (Explanatory variable) ".

  “Learning data ID” indicates identification information for identifying learning data for generating a model. Note that the learning data is accumulated for each user, for example. “User ID” corresponds to the similar item shown in FIG.

  “Target date and time” indicates the date and time when the possibility of calling is determined. “Target day of the week” indicates the day of the week for which the possibility of a call has been determined.

  “Call result information (objective variable)” is result information indicating whether the answer is correct or incorrect at the date and time of determination. For example, if the user made a call in response to the call at the date and time when the determination was made, “1” is stored in the call result information. On the other hand, if the user does not respond in response to the call and the call is not made at the date and time when the determination is made, “0” is stored in the call result information. Note that the result information is not limited to the above example. For example, when the determination apparatus 100 determines whether the user has a call possibility based on “Yes” or “No”, the result information includes the determination. Information regarding whether or not the determination is correct (whether "1" is stored in this case) or incorrect (in this case, "0" is stored) may be stored.

  “Usage status data (explanatory variable)” indicates usage status data of the user terminal 10 at the date and time of determination. In the example of FIG. 8, the usage status data is conceptually expressed as “G01”, but actually, the usage status data is data in which a plurality of usage statuses of the user terminal 10 are listed. Is memorized. That is, the usage status data is a collection of feature information extracted from the usage status of the user terminal 10 and includes all usage statuses used for determining the user's call possibility.

  That is, in the example of the data illustrated in FIG. 8, the learning data E01 identified by the learning data ID “E01” indicates that the learning target is the user U01. As an example of the learning data included in the learning data E01, the target date and time of determination is “April 13, 2017 12:00”, the target day of the week is “Thursday”, and the usage status data is “G01”. And the call result information at that time is “1”. More specifically, in the user U01, when the usage status data at the target date and time is “G01”, it indicates that the user U01 made a call in response to the call.

(About the model table 127)
Next, FIG. 9 shows an example of the model table 127 according to the embodiment. FIG. 9 is a diagram illustrating an example of the model table 127 according to the embodiment. As illustrated in FIG. 9, the model table 127 includes items such as “model ID” and “user ID”.

  “Model ID” indicates identification information for identifying a model. “User ID” indicates identification information for identifying a user corresponding to the model.

  That is, in the example of the data illustrated in FIG. 9, the model M01 identified by the model ID “M01” is a model corresponding to the user U01, and the model M02 identified by the model ID “M02” is assigned to the user U02. It shows that it is a corresponding model. As shown in FIG. 9, a model is generated for each user.

(About call mode storage unit 129)
The call mode storage unit 129 stores information related to a mode of calling the user, which is information provided from the determination apparatus 100 to the caller. For example, the information stored in the call mode storage unit 129 is a list indicating the possibility of each user's call to the caller, and for the caller to recognize which schedule should be called. Information. FIG. 10 shows an example of the call appearance storage unit 129 according to the embodiment. FIG. 10 is a diagram illustrating an example of the call appearance storage unit 129 according to the embodiment. As illustrated in FIG. 10, the call mode storage unit 129 includes items such as “caller ID”, “target date / time”, “call target user ID”, and “call possibility”.

  “Caller ID” indicates identification information for identifying a caller who performs a call. The caller shown in FIG. 10 is, for example, a business operator who calls the user to confirm the identity of the user when a predetermined application is received from the user, a business operator who conducts business by telephone, or a reminder. There are various business operators such as business operators.

  “Target date and time” indicates the date and time that is a target for determining the user's call possibility. For example, the target date and time is set based on a request from the service. Specifically, when the determination apparatus 100 receives a request from the caller about the possibility of calling each user on “April 30, 2017, 12:00”, the target date and time is set to “ "Month 30th 12:00" is set, and the possibility of a call is determined.

  Note that the target date and time may not be the timing itself for performing the determination process, but may be a deadline time for outputting the determination result. For example, in the example of FIG. 10, the determination apparatus 100 repeatedly obtains the usage status of the user terminal 10 and determines the call possibility until immediately before “April 30, 2017, 12:00”. Specifically, at the time of “April 30, 2017 12:00”, the determination result of the user's call possibility may be output.

  The “calling target user ID” indicates identification information for identifying a user to be called. “Call possibility” indicates the possibility of a call for each user. For example, the “callability” normalizes the score calculated by the determination apparatus 100 and stores a numerical value expressed as a percentage. Note that a fixed numerical value is not necessarily stored in the call possibility and may be updated each time the determination process is performed based on the acquired usage status until the determination date and time elapses.

  That is, in the example of the data shown in FIG. 10, regarding the customer user of the caller H01 identified by the caller ID “H01”, the possibility of a call at the target date “April 30, 2017 12:00” The example which performed determination is shown. As a result of the determination, for example, the call possibility of the user U13 identified by the call target user ID “U13” is “85”%, and the call possibility of the user U08 is “83”%. It shows that it was derived.

(About the control unit 130)
Returning to FIG. 3, the description will be continued. The control unit 130 is, for example, a controller, and includes various programs (an example of a determination program) stored in a storage device inside the determination apparatus 100 by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. This is realized by executing the RAM as a work area. The control unit 130 is a controller, and is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As illustrated in FIG. 3, the control unit 130 includes an acquisition unit 131, a determination unit 132, a generation unit 133, a determination unit 134, and a transmission unit 135, and functions and functions of information processing described below. Realize or execute. Note that the internal configuration of the control unit 130 is not limited to the configuration illustrated in FIG. 3, and may be another configuration as long as the information processing described below is performed. Further, the connection relationship between the processing units included in the control unit 130 is not limited to the connection relationship illustrated in FIG. 3, and may be another connection relationship.

(About the acquisition unit 131)
The acquisition unit 131 acquires various types of information. For example, the acquisition unit 131 acquires the usage status of the user terminal 10 used by the user.

  Specifically, the acquisition unit 131 acquires information detected by the user terminal 10 from the user terminal 10. For example, the acquisition unit 131 acquires position information of the user terminal 10. Further, the acquisition unit 131 may acquire position information indicating a position serving as a user's base, such as position information indicating the position of the user's home, position information indicating the position of the work place, and the like. For example, the acquisition unit 131 specifies the user's home or work place based on information registered in the service, and acquires position information of the specified position.

  Further, the acquisition unit 131 may acquire time information that is estimated to elapse when the user moves from the position indicated by the acquired position information to the user's home. For example, the acquisition unit 131 acquires time information estimated to elapse when the user moves by acquiring distance information between position information indicating the current location where the user is located and position information indicating the user's home. get. In this case, for example, the acquisition unit 131 may estimate the user's moving means from the transition of the position information, and estimate the time required for the movement, assuming that the estimated moving means is adopted. Thereby, the acquisition unit 131 can estimate whether or not the user is at home at the target date and time, and can use the information for the call possibility determination.

  Further, the acquisition unit 131 can acquire more accurate time information depending on the service used by the user. For example, when the car navigation application is executed on the user terminal 10, the acquisition unit 131 moves from the service server 30 that provides the car navigation application or the user terminal 10 on which the car navigation application is executed to the home. It is possible to acquire time information estimated to elapse in some cases.

  Further, the acquisition unit 131 acquires operation information indicating the physical operation of the user with respect to the user terminal 10 as the usage status. Specifically, the acquisition unit 131 acquires operation information that the user is touching the user terminal 10 and operation information that the user is holding the user terminal 10.

  Note that the acquisition unit 131 may acquire the estimated information by estimating the user's motion as described above from the acceleration information and the tilt information detected by the user terminal 10. Various known techniques may be used for such estimation.

  Moreover, the acquisition part 131 may acquire the operation information which shows whether the user is operating the user terminal 10 as a utilization condition. For example, when the user terminal 10 is equipped with a touch panel, the acquisition unit 131 acquires operation information indicating that the user is operating the touch panel.

  Moreover, the acquisition part 131 acquires the acceleration in the user terminal 10, or the moving speed of the user terminal 10 as a utilization condition. Note that the acquisition unit 131 may acquire not only specific values of acceleration and movement speed but also a context estimated from the acceleration and movement speed, such as that the user is moving by train or airplane. In this case, the acquisition unit 131 combines the acquired position information with map information provided by the service, and when it is estimated that the user is moving on the track, “the user is on the train” It may be estimated that the user is in the context of “

  Moreover, the acquisition part 131 may acquire the illumination intensity information in the periphery of the user terminal 10 as a utilization condition. Note that the acquisition unit 131 may acquire a context estimated from the illuminance information, such as that the user terminal 10 is in a cage, based on the illuminance information around the user terminal 10.

  Further, the acquisition unit 131 may acquire connection information indicating whether or not an audio output device is connected to the user terminal 10 as the usage status. In addition, the acquisition unit 131 may acquire the usage status such as music being played on the user terminal 10. When an audio output device such as an earphone is connected, it can be said that the user is highly likely to perceive a ringtone that is applied to the user terminal 10. For this reason, when the audio output device is connected to the user terminal 10 and music is being reproduced, it is estimated that the user has a high probability of responding to the call.

  In addition, the acquisition unit 131 may acquire application operation information that is information related to an application operation on the user terminal 10 as the usage status. For example, when the user is operating an application, it is estimated that the user is looking at the display screen of the user terminal 10, so that the user is likely to perceive a call to the user terminal 10. I can say that. For this reason, when the user terminal 10 is operating the application, it is estimated that the user has a higher probability of responding to the call.

  In addition, the acquisition unit 131 may acquire identification information that identifies an application that the user is operating, or an application category. For example, the probability that the user responds to the call may change depending on the type and category of the application. For example, a user who concentrates and operates a game application or the like may not respond to a call during operation of the application. In this way, by determining the relationship between the type of application and the category for each user, the determination unit 132 described later can determine the possibility of a call with higher accuracy.

  Moreover, the acquisition part 131 may acquire the utilization information regarding the service which the user utilized via the user terminal 10 as a utilization condition. Specifically, the acquisition unit 131 is a service that can be used via a network, and acquires, for example, a usage status of a web service that is used via the user terminal 10. The service is not limited to a web service, and may be a service used via an application installed in the user terminal 10, for example.

  For example, the acquisition unit 131 may acquire information related to a delivery schedule specified by the user in using a purchase-related service (for example, a shopping service or an auction service). For example, when the user orders a product, the acquisition unit 131 acquires information related to the schedule specified as the delivery date.

  Further, the acquisition unit 131 may acquire schedule information registered by the user when using a service related to schedule management (for example, a calendar service or a task management service). For example, the acquisition unit 131 acquires a predetermined schedule registered by the user in the service as schedule information.

  In addition, the acquisition part 131 may acquire not only the information regarding a schedule but various information as schedule information. For example, when a location is registered in the schedule, the acquisition unit 131 may acquire location information regarding the location. In this case, in the determination process to be described later, for example, if the place where the schedule is registered is the user's home or the like, it can be determined that the user's call possibility is relatively high at the registered date and time. Alternatively, if the place where the schedule is registered is other than the user's home, it is possible to determine that the user's call possibility is relatively low at the registered date and time.

  Moreover, the acquisition part 131 may acquire the information regarding the reservation schedule which the user reserved in the utilization of the service which concerns on at least any one of a transportation, a travel, a dining facility, or an accommodation facility. Note that the acquisition unit 131 may acquire position information as reservation information in the same manner as the schedule information.

  Moreover, the acquisition part 131 may acquire the information regarding a user's occupation or working time among the attribute information which the user registered into the service as a usage condition in a service.

  The acquisition unit 131 may be an information device used for using a service, and may acquire information related to a communication state in an information device installed at a user's home. For example, the acquisition unit 131 acquires information regarding a communication state such that near field communication is performed between the user terminal 10 carried by the user and an IoT device installed at the user's home. Note that the acquisition unit 131 is not limited to a home, and may acquire the communication status with information devices and access points installed in various places. Thereby, even when the user is out, the acquisition unit 131 can acquire information such as at which position communication is performed, and as a result, the acquisition unit 131 can acquire the position where the user is located. it can.

  Note that the acquiring unit 131 may appropriately acquire any usage status used for the call possibility determination element even in usage statuses other than those exemplified above. The acquisition unit 131 stores the acquired information in the usage status storage unit 121.

(About determination unit 132)
The determination unit 132 determines the call possibility of the user at a predetermined timing based on the relationship between the usage status acquired by the acquisition unit 131 and the user's call possibility. For example, the determination unit 132 refers to the definition table 124 in which information defining the relationship between the usage status of the user terminal 10 and the call possibility is described, and determines the call possibility of the user.

  For example, the determination unit 132 determines the user's call possibility based on the user's position information. As an example, the determination unit 132 determines the call possibility of the user based on whether or not the position information acquired by the acquisition unit 131 at the target date and time is position information indicating the position of the user's home. Specifically, the determination unit 132 determines that the user's call possibility is relatively high when the position information of the user acquired from the user terminal 10 indicates the vicinity of the user's home.

  Alternatively, the determination unit 132 compares the user's call possibility because it is generally difficult for the user to respond to the call when the user's position information indicates the user's work place or the like. It may be determined to be low.

  In addition, when the time information estimated to elapse when the user moves from the position indicated by the acquired position information to the user's home is acquired, the determination unit 132 acquires a predetermined time based on the time information. You may determine the possibility of a user's telephone call later. That is, the determination unit 132 says that the user is located in a range where the user can reach the home by moving from the current time to the target date and time, for example, even if information indicating that the user is located at the current date and time is not obtained. If the information is obtained, the user's call possibility after a predetermined time (that is, the target date and time) is determined to be high.

  The determination unit 132 may determine the possibility of a call based on information detected by the user terminal 10. For example, the determination unit 132 may determine the user's call possibility based on operation information indicating the user's physical operation with respect to the user terminal 10. For example, the determination unit 132 determines the user's call possibility when the situation that the user is holding the user terminal 10 is acquired based on inclination information or pressure information detected by the user terminal 10. You may judge comparatively high.

  Moreover, the determination part 132 may determine a user's call possibility based on the operation information which shows whether the user is operating the user terminal 10 or not. For example, when the user is operating the user terminal 10, the determination unit 132 may determine that the user's call possibility is relatively high because the probability of the user responding to the call is high.

  Further, the determination unit 132 may determine the user's call possibility based on the acceleration at the user terminal 10 or the moving speed of the user terminal 10. For example, the determination unit 132 estimates the user context based on acceleration, speed information, and the like detected by the user terminal 10. Then, when the user is walking, the determination unit 132 may determine that the possibility of a call is relatively higher than when the user is on a train, a car, an airplane, or the like.

  Further, the determination unit 132 may determine the user's call possibility based on the illuminance information around the user terminal 10. For example, the determination unit 132 has a higher probability that the user will respond to the call in a situation where the same illuminance as the outside environment is observed than in a situation where the user terminal 10 is assumed to be in a cage. Assuming that the user's call possibility is relatively high.

  Further, the determination unit 132 may determine the user's call possibility based on connection information indicating whether or not an audio output device is connected to the user terminal 10. For example, when the user is listening to music using the user terminal 10, the determination unit 132 may determine that the possibility of a call is relatively high because the user has a high probability of responding to a call.

  Further, the determination unit 132 may determine a user's call possibility based on application operation information that is information related to an application operation on the user terminal 10. For example, when the user is operating the app, the determination unit 132 is likely to be paying attention to the screen, and it is assumed that the probability of responding to the call is high. May be determined relatively high.

  Further, the determination unit 132 may determine the user's call possibility based on identification information for identifying an application operated by the user or an application category. For example, the probability that the user responds to the call may change depending on the type and category of the application. For example, a user who concentrates and operates a game application or the like may not respond to a call during operation of the application. For this reason, the determination part 132 may determine the said user's call possibility comparatively low, for example, when the user made into the determination object has started the said game application.

  Further, the determination unit 132 may acquire usage information regarding the service used by the user via the user terminal 10 as the usage status.

  For example, when information related to a delivery schedule specified by the user in using a service related to purchase is acquired, the determination unit 132 may determine the user's call possibility based on the information related to the delivery schedule. In general, it can be said that a user is highly likely to respond to a call on the date and time when the user specified a delivery schedule. For this reason, the determination part 132 can determine a user's call possibility accurately by performing a determination process based on the information regarding a delivery schedule.

  Further, the determination unit 132 may determine the user's call possibility based on the schedule information when the schedule information registered by the user is acquired in the use of the service related to the schedule management. Generally, when a user registers a schedule, it is estimated that the possibility that the user is at home is low and the possibility of a call is also low. For this reason, the determination part 132 can determine a user's call possibility accurately by performing a determination process based on schedule information.

  In addition, the determination unit 132 may use a reservation schedule when information on a reservation schedule reserved by the user is acquired in the use of a service related to at least one of transportation, travel, a dining facility, or an accommodation facility. Based on the information regarding the user, the user's call possibility may be determined.

  Moreover, the determination part 132 may determine a user's call possibility based on the information regarding a user's occupation or working time. For example, the determination unit 132 specifies a time zone during which the user is working based on the job type or working time of the user, and determines that the possibility of a call is relatively low during the specified time. Moreover, the determination part 132 may estimate a user's commuting time based on a user's home and work location information. Furthermore, the determination unit 132 may estimate the timing at which the user goes to the office or the timing to go home based on the estimated commuting time and the user's working time. Then, the determination unit 132 determines that the possibility of a call is low at a time when the user is estimated to be away from the home, and the possibility of a call at a time when the user is estimated to have returned from the work place to the home. May be determined high.

  In addition, the determination unit 132 is an information device used for using the service, and when information regarding the communication status of the information device installed at the user's home is acquired, the determination unit 132 is based on the information regarding the communication status. The call possibility may be determined. Generally, when short-distance communication or the like is performed between the user terminal 10 assumed to be carried by the user and an information device installed at home, the user is assumed to be at home. For this reason, the determination part 132 can determine a user's call possibility accurately by performing a determination process based on the communication condition with the information equipment installed in the house.

  In the determination process, the determination unit 132 may perform the determination process by appropriately combining the above usage situations. For example, when the usage status that can be used for the determination overlaps at the date and time of the determination target, the determination unit 132 adds the scores corresponding to the overlapping usage status and determines the user's call possibility. To do. The determination unit 132 can improve the accuracy of determination by performing determination based on a plurality of usage situations that are assumed to indicate user behavior.

  Note that the determination unit 132 may determine a user's call possibility using a model generated by the generation unit 133 through a predetermined learning process and generated for each user.

  Moreover, the determination part 132 may determine a user's call possibility based on the past call response history. For example, the determination unit 132 may determine the user's call possibility for each day of the week. Moreover, the determination part 132 may determine a user's call possibility for every time slot | zone.

  That is, when there is a response history of the user on the same day in the past at the date and time to be determined, the determination unit 132 may estimate whether or not the user is at home based on the response history trend. Good. Similarly, when there is a response history of the user in the same time in the past (for example, a time zone corresponding to 10 minutes before and after the date of determination) in the determination target date and time, based on the response history trend The determination unit 132 may estimate whether the user responds even at the timing of the current determination. As will be described later, the determination unit 132 can perform determination using the model generated by the generation unit 133 in consideration of the past user's home tendency and the like as described above.

  In addition, the determination part 132 may determine the call possibility of the user who becomes the customer of the call contractor when the request is received from the call contractor, or can call the unspecified user at all times. Sex may be determined.

  For example, when the determination unit 132 receives a request from the caller and makes a determination, the determination unit 132 acquires, for example, a list of users to be determined and information on the date and time to be determined. And the determination part 132 determines the telephone possibility of the user made into determination object in the date / time made into determination object by having received the request | requirement. For example, the determination unit 132 receives a request from a caller who is going to make a call “one hour after the current time”. In this case, the determination unit 132 sets “one hour after the current time” as the determination target date and time (corresponding to the “target date and time” illustrated in FIG. 10). And the determination part 132 determines the telephone call possibility for the customer user of a telephone company.

(About the generator 133)
The generation unit 133 learns the relationship between the usage status acquired by the acquisition unit 131 and the result information indicating whether or not the user has made a call with respect to the call to the user. Generate a model that calculates callability. Specifically, the generation unit 133 determines whether the user has responded to the call based on the usage status used for the determination target and the result information in the determination. Learn the tendency to contribute to

  For example, a different score may be more appropriate for the call possibility score defined in advance for the usage situation depending on the user. Specifically, there are cases where the user to be judged is less likely to respond to a call in the situation of being at home, or more likely to respond to a call in the situation of being at work. is there. Thus, even when the same usage status is acquired for each user, it is assumed that the usage status that contributes to determine the possibility of a call varies depending on each user.

  Therefore, the generation unit 133 acquires result information (that is, correct answer data) such as whether or not the user actually responded to the call, and learns the relationship between the use situation used for the determination and the result, A model reflecting learning is generated for each user. Then, the determination unit 132 performs determination using the model generated by the generation unit 133. Thereby, the determination part 132 can improve the precision of determination more.

  The model generation will be specifically described below. Note that the learning methods and models shown below are examples, and the generation unit 133 may generate any model using various known methods. That is, the generation unit 133 may use any learning method as long as it can feed back the result of whether or not the user has responded to the call to the determination process according to the embodiment.

  For example, the generation unit 133 sets the result information indicating whether or not the user has responded to the call at the date and time of determination as the objective variable in the regression analysis. And the production | generation part 133 makes the various utilization condition used for determination the explanatory variable in regression analysis. And the production | generation part 133 produces | generates the model for determining call possibility using an objective variable and an explanatory variable. In the example described below, the usage status described in the definition table 124 shown in FIG. 7 is used for processing, but the numerical value of each score is not considered. Further, in the following, an example is shown in which learning is performed with a case where the user responds to the call as a positive example and a case where the user does not respond as a negative example.

  For example, the generation unit 133 generates an expression indicating the relationship between whether or not the user actually responded to the call and the usage situation used for the determination. Further, the generation unit 133 calculates what weight each usage situation has for an event that the user responds to the call. Thereby, the production | generation part 133 can acquire the information of how much each explanatory variable contributes with respect to the event that a user responds to a call. For example, the generation unit 133 generates the following equation (1) when generating a model related to the user U01 which is an example of the user.

y _{(user U01)} = ω ₁ · x ₁ + ω ₂ · x ₂ + ω ₃ · x ₃ ... + ω _N · x _N (1) (N is an arbitrary number)

In the above equation (1), “y _{(user U01)} ” indicates an event “whether or not the user U01 actually responded to the call”. For example, in the example of the above formula (1), “y” is represented by “1” (responded) or “−1” (not responded). Note that the generation unit 133 may appropriately use a numerical value other than “−1” and “1” as the value of y in order to facilitate calculation.

In the above formula (1), “x” is an explanatory variable and corresponds to the usage status of the user terminal 10. Specifically, “x ₁ ” in the above formula (1) is position information of the user U01 (more specifically, “position information indicating that he / she is at home”). For example, “x ₁ ” indicates whether or not position information of the vicinity of the home of the user U01 is acquired at the date and time of determination.

In addition, “x ₂ ” in the formula (1) is operation information for operating the user terminal 10. For example, “x ₂ ” indicates whether or not the user U01 is operating the user terminal 10 at the date and time of determination.

In addition, “x ₃ ” in the equation (1) is information regarding the delivery schedule of the user U01 in the service. For example, “x ₃ ” indicates whether or not the user U01 has designated delivery of goods at the date and time of determination. That is, the right side of the above equation (1) corresponds to the presence / absence of various usage situations of the user terminal 10 as shown in FIG.

In the above formula (1), “ω” is a coefficient of “x” and indicates a predetermined weight value. Specifically, “ω ₁ ” is a weight value of “x ₁ ”, “ω ₂ ” is a weight value of “x ₂ ”, and “ω ₃ ” is a weight value of “x ₃ ”. It is. Thus, the above equation (1) is obtained by combining the variable (for example, “ω ₁ · x _1” ) including the explanatory variable “x” corresponding to the use situation and the predetermined weight value “ω”. Created.

  For example, it is assumed that the date and time of determination is “T1”. It is assumed that the information acquired as the usage status in the service of the user U01 at T1 is “location information indicating staying home” and “designation of delivery schedule”. In T1, it is assumed that the usage status corresponding to the explanatory variable “operation information” has not been acquired. In T1, it is assumed that a result that the user U01 “responds to the call” is obtained as a result. In this case, the above formula (1) is expressed as the following formula (2).

y (= 1) _{(users U01, T1)} = ω ₁ × x ₁ (position information indicating that they are at home = 1) + ω ₂ × x ₂ (operation information = 0) + ω ₃ × x ₃ (delivery) Designation of schedule = 1) (2)

As shown in the above equation (2), a value of “0” is substituted for “x ₂ ” for which the usage status has not been acquired. In this case, at least the information that contributed to the determination of the positive example (y = 1) is “location information indicating staying home” or “designation of delivery schedule”.

  Further, the date and time of the determination target is temporarily “T2”. In T2, it is assumed that the information acquired as the usage status in the service of the user U01 is “location information indicating that the user is at home” and “operation information”. In T2, it is assumed that the usage status corresponding to the explanatory variable “designation of delivery schedule” has not been acquired. In T2, it is assumed that the result is that the user U01 “has not responded to the call” as a result. In this case, the above formula (1) is expressed as the following formula (3).

y (= 1) _{(users U01, T2)} = ω ₁ × x ₁ (position information indicating that they are at home = 1) + ω ₂ × x ₂ (operation information = 1) + ω ₃ × x ₃ (delivery) Designation of schedule = 0) (3)

As shown in the above equation (3), a value of “0” is substituted for “x ₃ ” for which the usage status has not been acquired. In this case, at least the information that contributed to the determination of the negative example (y = −1) is “position information indicating that the user is at home” and “operation information”.

  And the production | generation part 133 produces | generates a formula for every date and time of determination object like said Formula (2) and (3), and makes the produced | generated formula the sample of regression analysis. Then, the generation unit 133 derives a value corresponding to the predetermined weight value “ω” by performing calculation processing of the sample expression. Moreover, the production | generation part 133 produces | generates the formula used as a sample like said Formula (2) at any time. Then, the generation unit 133 recursively determines a predetermined weight value “ω” that satisfies the expressions (2) and (3) according to the increase in the generated expressions. In other words, the generation unit 133 determines the weight value “ω” indicating the influence of the predetermined explanatory variable on the objective variable “y”.

If the user U01 has responded to the call “responds to the call” and the “location information indicating that he / she is at home” contributes compared to other variables, the “at home” The value of the weight value “ω ₁ ” corresponding to “positional information indicating that” is estimated to be a large positive value compared to other variables. This indicates that, when the user U01 is at home, the user U01 is a user who tends to respond to the call relatively.

Further, if the “operation information” contributes to the event that the user U01 “has not responded to the call” compared to other variables, the weight corresponding to the “operation information” The value “ω ₂ ” is estimated to be a large negative value compared to other variables. This indicates that, when the user U01 is operating the user terminal 10, the user U01 is a user who tends to be relatively difficult to respond to a call.

Also, if “Usage of delivery schedule” contributes to the event that user U01 “Responded to call” compared to other variables, it corresponds to “Designation of delivery schedule”. It is estimated that the value of the weight value “ω ₃ ” to be calculated is a large positive value compared to other variables. This indicates that the user U01 is a user who is relatively apt to respond to calls on the date and time when the user U01 designates a delivery schedule for goods and the like. Also, if “delivery schedule specification” does not contribute to the call response response of user U01 compared to other variables, the weight value corresponding to “delivery schedule specification” The value of “ω ₃ ” is estimated to gradually approach “0” as learning progresses.

  In the above example, three types of usage situations are shown as explanatory variables. Actually, however, the above formulas (2) and (3) have various usage situations corresponding to various usage situations acquired by the acquisition unit 131. The explanatory variables are included. That is, the generation unit 133 generates a model using various information extracted from the usage situation as illustrated in FIGS. 5, 6, 7, and the like as explanatory variables.

  As described above, the generation unit 133 generates a model that associates an event whether or not a user responds to a call with a usage state of the user terminal 10. In the calculation process using the above formula (2), the left side is not set to “1” or “−1”, but a predetermined error is assumed, and a value obtained by squaring the difference from the error is the minimum value. The optimal solution of “ω” may be calculated using a method such as a least square method that approximates to

  In addition, when substituting information extracted from the usage status into the generated model, the generation unit 133 determines whether the variable is determined to be “present” or “not present” such as “designation of delivery schedule”. A numerical value of “1” or “0” is substituted. Further, for the dynamic value such as the position information, the generation unit 133 may appropriately substitute a numerical value corresponding to the distance to the home, for example. For example, the generation unit 133 may apply various known methods, such as normalizing information indicating a usage situation that can be an explanatory variable such as position information so that it can be handled by a model, according to a known method. .

  The generation unit 133 may update the model as needed when the acquisition unit 131 acquires a new usage state after generating the model. Thereby, the production | generation part 133 can optimize the model for determining a user's call possibility.

  In addition, as described above, the generation unit 133 may reflect the learning result in the definition table 124 when learning the relationship between the usage state and the call possibility. As described above, the generation unit 133 sets a value (in this example, the weight value ω) that contributes to whether each usage state responds to the call to a positive value or a negative value. Can be shown. For this reason, the generation unit 133 can give an appropriate score even for a usage situation that is not defined in advance, for example, by calculating a score corresponding to each usage situation based on the calculated weight value. . More specifically, according to learning, a usage score that contributes to the determination that the user responds to the call is given a positive score, and a use situation that contributes to the determination that the user does not respond to the call Given a negative score.

  The generation unit 133 stores information related to learning and the generated model in the model storage unit 125. And the determination part 132 may perform determination using the model like said Formula (1) by which the weight value was substituted as a result of learning, and the score was defined (adjusted) according to the user. The determination may be made using information in the definition table 124.

  In addition, the production | generation part 133 does not necessarily need to make the result information at the time of a call by the caller the correct data. For example, the generation unit 133 generates a model of the determination target user based on the result information of other users having attributes similar to the determination target user and the result information of customer users of the same caller. Also good. Thereby, since the production | generation part 133 can learn even if it is not actually called by a user, it can compensate for the shortage of the number of samples of result information.

(About the determination unit 134)
The determination unit 134 determines a call mode for the user based on the user's call possibility determined by the determination unit 132.

  For example, the determination unit 134 determines the order in which calls are made to the determination target user based on the call possibility of all customer users of the caller as a call form. Specifically, the determination unit 134 sorts the call possibilities of the caller customer users in descending order at the determination target date and time. Then, the determination unit 134 creates a transmittable file using the sorted information as a list.

  In addition, the determination unit 134 may determine a schedule such as which timing to call for a user who is a determination target. That is, the determination unit 134 extracts the date and time when the user is likely to talk among the several determination target dates and times determined by the determination unit 132. And the determination part 134 determines what kind of timing (schedule) should be telephoned with respect to the said user by sorting the date with high possibility of telephone call in order.

  When the determination unit 134 determines a mode for providing a predetermined service, the determination unit 134 transmits the determined information to the transmission unit 135.

(About transmitter 135)
The transmission unit 135 transmits information regarding the mode determined by the determination unit 134 to a provider who provides a predetermined service.

  For example, the transmission unit 135 transmits a list indicating the order of users who should call the customer user to the customer user in a certain time period. Or the transmission part 135 transmits the list | wrist which showed the schedule suitable as a timing to call about a certain user to a caller.

[4. Configuration of user terminal]
Next, the configuration of the user terminal 10 according to the embodiment will be described with reference to FIG. FIG. 11 is a diagram illustrating a configuration example of the user terminal 10 according to the embodiment. As illustrated in FIG. 11, the user terminal 10 includes a communication unit 11, an input unit 12, a display unit 13, a detection unit 14, a storage unit 15, and a control unit 16. Note that the connection relationship between the processing units included in the user terminal 10 is not limited to the connection relationship illustrated in FIG. 11, and may be another connection relationship.

  The communication unit 11 is connected to the network N by wire or wireless, and transmits / receives information to / from the service server 30 and the determination apparatus 100. For example, the communication unit 11 is realized by a NIC or the like.

  The input unit 12 is an input device that receives various operations from the user. For example, the input unit 12 is realized by an operation key or the like provided in the user terminal 10. The input unit 12 may include an imaging device (such as a camera) for capturing an image and a sound collection device (such as a microphone) that collects sound.

  The display unit 13 is a display device for displaying various information. For example, the display unit 13 is realized by a liquid crystal display or the like. In addition, when a touch panel is employ | adopted for the user terminal 10, a part of input part 12 and the display part 13 are integrated.

  The detection unit 14 detects various operations on the user terminal 10 and environmental information around the user terminal 10. For example, the detection unit 14 is realized by a sensor or an antenna that detects various types of information. Specifically, the detection unit 14 includes a communication status related to a device connected to the user terminal 10, illuminance and noise around the user terminal 10, physical movement of the user terminal 10, position information of the user terminal 10, and the like. Is detected.

  For example, the detection unit 14 detects a user operation based on information input to the input unit 12. In other words, the detection unit 14 detects that there has been an input of an operation for touching the screen to the input unit 12, an input of a voice, or the like. Moreover, the detection part 14 may detect that the predetermined application was started by the user. When such an application is an application that operates an imaging function (for example, a camera) in the user terminal 10, the detection unit 14 detects that the imaging function is used by the user. Further, the detection unit 14 may detect an operation in which the user terminal 10 itself is moved based on data detected by an acceleration sensor, a gyro sensor, or the like provided in the user terminal 10. For example, the detection unit 14 detects the tilt information of the user terminal 10 based on data detected by a gyro sensor or the like, and the user terminal 10 is in the user's hand or the user terminal 10 is in the user's hand. Detecting that you are handling.

  Further, the detection unit 14 detects the current position of the user terminal 10. Specifically, the detection unit 14 receives radio waves transmitted from a GPS (Global Positioning System) satellite, and obtains position information (for example, latitude and longitude) indicating the current position of the user terminal 10 based on the received radio waves. get.

  In addition, the detection part 14 may acquire position information by various methods other than GPS. For example, when the user terminal 10 has a function equivalent to that of a contactless IC card used at a station ticket gate or a store (or the user terminal 10 has a function of reading a history of the contactless IC card) ), The used position is recorded together with the information on the settlement of the boarding fee at the station by the user terminal 10. The detection unit 14 detects such information and acquires it as position information. Moreover, the detection part 14 may detect the positional information acquirable from an access point, when the user terminal 10 communicates with a specific access point. The position information may be acquired by an optical sensor, an infrared sensor, a magnetic sensor, or the like included in the user terminal 10.

  The detection unit 14 detects an external device connected to the user terminal 10. For example, the detection unit 14 detects the external device based on exchange of communication packets with the external device, a signal generated by the external device, and the like. Specifically, the detection unit 14 detects radio waves such as WiFi and Bluetooth used by the external device. The detection unit 14 may detect the type of connection with the external device when communication with the external device is established. For example, the detection unit 14 detects whether it is connected to an external device by wire or wireless communication. Moreover, the detection part 14 may detect the communication system etc. which are used by radio | wireless communication. The detection unit 14 may detect the external device based on information acquired by a radio wave sensor that detects a radio wave emitted by the external device, an electromagnetic wave sensor that detects an electromagnetic wave, or the like. An example of the external device is another device (another user terminal 10) used by a user who uses the user terminal 10, and is, for example, a wearable device or a stationary IoT device.

  In addition, the detection unit 14 detects an environment in the user terminal 10. The detection unit 14 uses various sensors and functions provided in the user terminal 10 to detect information about the environment. For example, the detection unit 14 is a microphone that collects sound around the user terminal 10, an illuminance sensor that detects illuminance around the user terminal 10, and an acceleration sensor that detects physical movement of the user terminal 10 (or A gyro sensor), a humidity sensor that detects the humidity around the user terminal 10, a geomagnetic sensor that detects a magnetic field at the location of the user terminal 10, and the like. And the detection part 14 detects various information using various sensors. For example, the detection unit 14 detects a noise level around the user terminal 10 and an illuminance level around the user terminal 10. Further, the detection unit 14 may detect surrounding environment information based on a photograph or video taken by the camera.

  The user terminal 10 may acquire context information indicating the context of the user terminal 10 based on information detected by the detection unit 14. As described above, the user terminal 10 has various sensors such as position, acceleration, temperature, gravity, rotation (angular velocity), illuminance, geomagnetism, pressure, proximity, humidity, and rotation vector by various built-in sensors (detection unit 14). Is obtained as context information. In addition, the user terminal 10 may acquire, as context information, a connection status (for example, information regarding establishment of communication or a communication standard used) with various devices by using a built-in communication function. .

(About the storage unit 15)
The storage unit 15 stores various information. The storage unit 15 is realized by, for example, a semiconductor memory device such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 15 includes a service information storage unit 151.

  The service information storage unit 151 stores, for example, information related to services used by the user. Specifically, the service information storage unit 151 stores an action history (log) in the service used by the user. For example, the service information storage unit 151 stores a usage history of applications installed in the user terminal 10. Note that the user terminal 10 may upload the information stored in the service information storage unit 151 to the determination apparatus 100 at regular intervals, for example, in accordance with an instruction from the determination apparatus 100.

  The control unit 16 is a controller, and is realized, for example, by executing various programs stored in a storage device inside the user terminal 10 using the RAM as a work area by a CPU, an MPU, or the like. The control unit 16 is a controller, and is realized by an integrated circuit such as an ASIC or FPGA, for example.

  The control unit 16 controls various processes performed in the user terminal 10. As illustrated in FIG. 11, the control unit 16 includes a reception unit 161, an acquisition unit 162, and a transmission unit 163, and implements or executes information processing functions and operations described below.

  The receiving unit 161 receives various information. For example, the reception unit 161 receives information transmitted from the service server 30 or the determination device 100. The receiving unit 161 receives various information detected by the detecting unit 14.

  The acquisition unit 162 acquires various information and data. For example, the acquisition unit 162 acquires the web page that the user desires to browse by accessing the service server 30. In addition, the acquisition unit 162 acquires information about various applications via an application download site or the like.

  The transmission unit 163 transmits various information. For example, the transmission unit 163 transmits information regarding the usage status of the user terminal 10 detected by the detection unit 14 to the service server 30 and the determination device 100. Further, the transmission unit 163 refers to the storage unit 15 and the like, and transmits information regarding the usage status of the user terminal 10 accumulated in the user terminal 10 to the determination apparatus 100.

[5. Processing procedure)
Next, a processing procedure performed by the determination apparatus 100 according to the embodiment will be described with reference to FIGS. 12 to 14. First, a processing procedure for determining a call possibility will be described with reference to FIG. FIG. 12 is a flowchart (1) illustrating a processing procedure according to the embodiment.

  As illustrated in FIG. 12, the determination apparatus 100 acquires the usage status of the user terminal 10 (step S101). Then, the determination apparatus 100 determines whether or not the set target date and time (timing for determining call possibility) has arrived (step S102). When the set target date / time has not arrived (step S102; No), the determination apparatus 100 stands by until the set target date / time arrives, and continues the process of acquiring the usage status of the user terminal 10. .

  On the other hand, when the set target date and time has arrived (step S102; Yes), the determination apparatus 100 refers to the relationship between the usage status and the call possibility by referring to the definition table 124, for example (see FIG. Step S103).

  Subsequently, the determination apparatus 100 calculates a score serving as an index value indicating the possibility of a call for each user based on the referred information (step S104). And the determination apparatus 100 determines a user's call possibility based on the calculated score (step S105). Furthermore, the determination apparatus 100 determines the mode of calling for the user based on the determination result (step S106). Subsequently, the determination apparatus 100 transmits the determined mode to the caller (step S107).

  Next, a processing procedure related to model generation will be described with reference to FIG. FIG. 13 is a flowchart (2) illustrating a processing procedure according to the embodiment.

  After the call is made, the determination apparatus 100 acquires result information about the call (step S201). Then, the determination apparatus 100 determines whether or not result information sufficient for learning has been accumulated (step S202). When the result information sufficient for learning is not accumulated (step S202; No), the determination apparatus 100 continues the process of acquiring the result information.

  On the other hand, when the result information sufficient for learning is accumulated (step S202; Yes), the determination apparatus 100 generates a model for each user based on the learning result (step S203). And the determination apparatus 100 matches the produced | generated model for every user, and stores it in the memory | storage part 120 (step S204).

  Next, a processing procedure related to model update will be described with reference to FIG. FIG. 14 is a flowchart (3) illustrating a processing procedure according to the embodiment.

  The determination apparatus 100 determines whether or not a determination request has been received from, for example, a caller (step S301). When the determination request is not received (step S301; No), the determination apparatus 100 waits until the determination request is received.

  On the other hand, when the determination request is received (step S301; Yes), the determination apparatus 100 acquires the usage status used for the determination (step S302). And the determination apparatus 100 inputs the acquired use condition into a model, and determines the call possibility of the said user using the model corresponding to a user (step S303).

  Thereafter, the determination apparatus 100 determines whether or not the result information has been acquired (step S304). When the result information is not acquired (step S304; No), the determination apparatus 100 waits until acquisition. On the other hand, when the result status is acquired (step S304; Yes), the determination apparatus 100 updates the model based on the acquired result information (step S305). The determination apparatus 100 generates a model optimized for each user by repeating the processing from step S301 to step S305.

[6. (Modification)
The determination apparatus 100 described above may be implemented in various different forms other than the above embodiment. Therefore, in the following, another embodiment of the determination apparatus 100 will be described.

[6-1. Usage situation〕
The determination apparatus 100 may acquire various usage situations other than the usage situations exemplified in the above-described embodiment.

  For example, the determination apparatus 100 may acquire the user's SNS writing or SNS posting information as the usage status in the service. For example, the location information of the user terminal 10 may be included in the writing to the SNS and post information.

  Further, the determination apparatus 100 may acquire schedule information from writing to the SNS or the like using text analysis or the like. For example, the SNS writing may include text such as “I went to AAA prefecture on the 20th” or “I went to BBB prefecture on the 15th”. The determination apparatus 100 may convert these texts into schedule information using morphological analysis or the like, and acquire the schedule information based on these texts. For example, if any schedule is scheduled, the user may be less likely to respond to the call at that date and time. The determination apparatus 100 may acquire such information from SNS writing or posting, and may use the acquired information as a determination element.

  Moreover, the determination apparatus 100 may acquire a search history or the like in the route search service as the usage status in the service. For example, when a user searches for a route in a region away from his / her home, it can be estimated that the user is not likely to be at home at the date and time related to the search. For this reason, the determination apparatus 100 may use the route search log as an element of the call possibility determination process.

  Further, the determination apparatus 100 may acquire a search history in the weather information service, etc., as the usage status in the service. For example, when the user searches for weather several days after the region away from home, it can be estimated that the user is not likely to be at home at the date and time related to the search. For this reason, the determination apparatus 100 may use the weather information service log as an element of the call possibility determination process.

  Further, the determination apparatus 100 may acquire information related to an application activated on the user terminal 10. For example, when the user is activating the car navigation application, it can be estimated that the user is likely not to respond to the call. Or when the user has started the application which operates the household appliance installed in the home, it can be estimated that the user is highly likely to be at home. As described above, the determination apparatus 100 may determine the possibility of a call based on the activation of the application and the operation information.

[6-2. Use of overall information)
In the said embodiment, the example which produces | generates the model corresponding to a user using the usage condition for every user was shown. Here, the determination apparatus 100 may perform a determination process that reflects a tendency or the like acquired from the entire user who is a determination target, as well as information about the individual user.

  For example, in determining the possibility of a call, it is assumed that what kind of information contributes more in the usage situation has a tendency for each individual and also for the entire user. For this reason, the determination apparatus 100 may perform learning of a specific user by using the relationship between the usage status of other users and the result information.

  For example, the determination apparatus 100 extracts a user having an attribute similar to the user to be determined. Specifically, the determination apparatus 100 extracts a user whose gender, age, place of residence, and the like are similar to the user to be determined. And the determination apparatus 100 produces | generates the formula which shows the relationship between the utilization condition acquired from the extracted user, and result information. And the determination apparatus 100 utilizes the produced | generated formula for the learning of the user used as determination object. Thereby, the determination apparatus 100 can generate a model reflecting not only an individual user but also the overall tendency.

[6-3. (Possibility of calling)
In the embodiment, an example is shown in which the call possibility is expressed as a percentage. However, the determination apparatus 100 does not necessarily need to indicate the call possibility at a ratio such as a percentage. For example, the determination device 100 does not indicate the possibility of a call with a specific numerical value, and may only indicate the relative call possibility (for example, the order in which calls are made) among all users who are to be called.

[6-4. (User terminal)
In the said embodiment, although the structural example of the user terminal 10 was shown using FIG. 11, the user terminal 10 does not necessarily need to have all the structures shown in FIG. As described above, the user terminal 10 includes not only smart devices such as smartphones and tablet terminals, but also various wearable devices such as eyeglass-type terminals having a communication function, or heart rate measuring devices for storing a user's heart rate. Is included. In this case, the user terminal 10 does not necessarily receive an input from the user, but may have a function of automatically acquiring the usage status of the user service and transmitting the acquired information to the communication network. That is, the user terminal 10 does not necessarily have the configuration illustrated in FIG. 11 as long as it is a device having a predetermined communication function that realizes so-called IoT.

[7. Hardware configuration)
The determination apparatus 100 and the user terminal 10 according to the above-described embodiments are realized by a computer 1000 having a configuration as shown in FIG. 15, for example. Hereinafter, the determination apparatus 100 will be described as an example. FIG. 15 is a hardware configuration diagram illustrating an example of a computer 1000 that implements the functions of the determination apparatus 100. The computer 1000 includes a CPU 1100, RAM 1200, ROM 1300, HDD 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores a program executed by the CPU 1100, data used by the program, and the like. The communication interface 1500 receives data from other devices via the communication network 500 (corresponding to the network N shown in FIG. 2) and sends the data to the CPU 1100, and the data generated by the CPU 1100 is transferred to other devices via the communication network 500. Send to device.

  The CPU 1100 controls an output device such as a display and a printer and an input device such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the data generated via the input / output interface 1600 to the output device.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

  For example, when the computer 1000 functions as the determination apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 130 by executing a program loaded on the RAM 1200. The HDD 1400 stores data in the storage unit 120. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from other devices via the communication network 500.

[8. Others]
In addition, among the processes described in the above embodiment, all or part of the processes described as being automatically performed can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method. In addition, the processing procedures, specific names, and information including various data and parameters shown in the document and drawings can be arbitrarily changed unless otherwise specified. For example, the various types of information illustrated in each drawing is not limited to the illustrated information.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. For example, the determination unit 132 and the determination unit 134 illustrated in FIG. 3 may be integrated. Further, for example, information stored in the storage unit 120 may be stored in a predetermined storage device provided outside via the network N.

  Moreover, in the said embodiment, the determination apparatus 100 showed the example which performs the acquisition process which acquires a utilization condition, the determination process which determines call possibility, and the production | generation process which produces | generates a model, for example. However, the determination apparatus 100 described above may be separated into an acquisition apparatus that performs an acquisition process, a determination apparatus that performs a determination process, and a generation apparatus that performs a generation process. In this case, the acquisition device includes at least the acquisition unit 131. The determination device has at least a determination unit 132. The generation apparatus has at least a generation unit 133. And the process by said determination apparatus 100 is implement | achieved by the determination processing system 1 which has each apparatus of a reception apparatus, a determination apparatus, and a delivery apparatus.

  In addition, the above-described embodiments and modifications can be combined as appropriate within a range that does not contradict processing contents.

[9. effect〕
As described above, the determination apparatus 100 according to the embodiment includes the acquisition unit 131 and the determination unit 132. The acquisition unit 131 acquires the usage status of the user terminal 10 used by the user. Based on the relationship between the usage status acquired by the acquisition unit 131 and the possibility of a call that is a possibility that the user will make a call with respect to the call, the determination unit 132 may determine whether the user can call at a predetermined timing. Determine.

  As described above, the determination device 100 according to the embodiment makes a request regarding the call timing to the caller by determining the possibility of the user's call based on the usage status in the user terminal 10, Even if the timing is not registered, the user's call possibility can be determined based on the daily situation of the user. Moreover, the determination apparatus 100 can determine real-time information by determining based on the usage status of the user terminal 10 to determine call possibility. Thereby, the determination apparatus 100 can accurately determine the possibility that a call with the user is established for the call.

  Moreover, the determination apparatus 100 according to the embodiment learns the relationship between the usage status acquired by the acquisition unit 131 and the result information indicating whether or not the user has made a call in response to the call to the user. Thus, a generation unit 133 that generates a model for calculating the user's call possibility is further provided. The determination unit 132 determines the user's call possibility using the model generated by the generation unit 133.

  As described above, the determination apparatus 100 according to the embodiment may determine a user's call possibility using a model in which a result of the call possibility is reflected by learning as well as a predefined relationship. Thereby, the determination apparatus 100 can determine the user's call possibility with high accuracy.

  Further, the determination unit 132 determines the possibility of the user's call based on the day of the week at a predetermined timing. Moreover, the determination part 132 determines a user's call possibility based on the time slot | zone of a predetermined timing.

  Thus, the determination apparatus 100 according to the embodiment determines the possibility of a call for each day of the week or time period. Thereby, since the determination apparatus 100 can determine based on the past user's action history etc., it can improve the precision of determination.

  Moreover, the acquisition part 131 acquires the positional information on the user terminal 10 as a utilization condition. The determination unit 132 determines the user's call possibility based on the position information.

  As described above, the determination apparatus 100 according to the embodiment can determine the user's call possibility based on the daily action information of the user such as the position information. Thereby, the determination apparatus 100 can perform the determination process without imposing a burden on the user such as registration of the call timing for the caller.

  Further, the determination unit 132 determines the user's call possibility based on whether or not the position information acquired by the acquisition unit 131 is position information indicating the position of the user's home.

  As described above, the determination apparatus 100 according to the embodiment determines whether or not the user is at home based on the position information, and then determines the user's call possibility. Thereby, the determination apparatus 100 can improve the determination accuracy.

  The acquisition unit 131 acquires time information that is estimated to elapse when the user moves from the position indicated by the position information to the user's home. The determination unit 132 determines a user's call possibility at a predetermined timing based on the time information.

  As described above, the determination apparatus 100 according to the embodiment is not limited to the position information at the timing to be determined, but the user's call is determined based on the position information acquired before the determination based on the user's possibility of being at home. The possibility may be determined. That is, the determination apparatus 100 can make a determination based not only on the determination timing but also on the usage status acquired at various timings.

  Further, the acquisition unit 131 acquires operation information indicating the physical operation of the user with respect to the user terminal 10 as the usage status. The determination unit 132 determines the user's call possibility based on the operation information.

  As described above, the determination apparatus 100 according to the embodiment may determine the possibility of a call based on the daily operation of the user. That is, since the determination apparatus 100 can use the user's natural behavior as a determination element instead of causing the user to consciously take any action, the determination apparatus 100 can perform a determination process without burden on the user.

  Moreover, the acquisition part 131 acquires the operation information which shows whether the user is operating the user terminal 10 as a utilization condition. The determination unit 132 determines a user's call possibility based on the operation information.

  As described above, the determination apparatus 100 according to the embodiment can improve the accuracy of the determination by determining the possibility of a call based on a situation where it is assumed that the user is likely to receive an incoming call.

  Moreover, the acquisition part 131 acquires the acceleration in the user terminal 10, or the moving speed of the user terminal 10 as a utilization condition. The determination unit 132 determines the user's call possibility based on the acceleration or the moving speed.

  As described above, the determination apparatus 100 according to the embodiment performs determination based on the user's situation (context) such as whether the user is using a transportation facility or is walking. Can be improved.

  Moreover, the acquisition part 131 acquires the illumination intensity information in the periphery of the user terminal 10 as a utilization condition. The determination part 132 determines a user's call possibility based on illumination intensity information.

  Thus, the determination apparatus 100 according to the embodiment can improve the accuracy of determination by estimating the situation in which the user is handling the user terminal 10 and performing the determination.

  In addition, the acquisition unit 131 acquires connection information indicating whether or not an audio output device is connected to the user terminal 10 as a usage status. The determination unit 132 determines the possibility of a user's call based on the connection information.

  As described above, the determination apparatus 100 according to the embodiment can improve the accuracy of determination by performing determination in consideration of a situation in which the user is listening to music using the user terminal 10.

  In addition, the acquisition unit 131 acquires application operation information that is information related to an application operation on the user terminal 10 as the usage status. The determination unit 132 determines the user's call possibility based on the application operation information.

  As described above, the determination apparatus 100 according to the embodiment uses a variety of determination elements to make a call by using the situation that the user is operating the app and the possibility of responding to a call as determination elements. The possibility can be determined.

  In addition, the acquisition unit 131 acquires identification information that identifies an application that the user is operating, or an application category. The determination unit 132 determines the call possibility of the user based on the identification information for identifying the application or the category of the application.

  Thus, the determination apparatus 100 according to the embodiment may perform determination for each type or category of application. As a result, the determination apparatus 100 responds to various user actions such as, for example, a user who operates a business-related application can easily answer a call, and a user who operates a game-related application cannot easily answer a call. The possibility of a call can be determined.

  Further, the acquisition unit 131 acquires usage information regarding the service used by the user via the user terminal 10 as the usage status.

  As described above, the determination apparatus 100 according to the embodiment makes a determination based on not only the status of the user terminal 10 itself but also the usage status of the service used via the user terminal 10, thereby providing more various elements. Can be used to make the determination.

  In addition, the acquisition unit 131 acquires information on a delivery schedule specified by the user in using a service related to purchase. The determination part 132 determines a user's call possibility based on the information regarding a delivery schedule.

  As described above, the determination apparatus 100 according to the embodiment may determine the user's call possibility in consideration of an event that is assumed to affect the possibility of responding to the call such as designation of a delivery schedule. Good. Thereby, the determination apparatus 100 can perform a determination process that accurately reflects the user's behavior.

  In addition, the acquisition unit 131 acquires information related to a reservation schedule reserved by the user in using a service related to at least one of transportation, travel, eating and drinking facilities, or accommodation facilities. The determination part 132 determines a user's call possibility based on the information regarding a reservation schedule.

  As described above, the determination apparatus 100 according to the embodiment may determine the user's call possibility in consideration of an event that is assumed to affect the possibility of responding to a call such as reservation information. Thereby, the determination apparatus 100 can perform a determination process that accurately reflects the user's behavior.

  Moreover, the acquisition part 131 acquires the information regarding a user's occupation or working time among the attribute information which the user registered into the service. The determination part 132 determines a user's call possibility based on a user's occupation or working time.

  As described above, the determination apparatus 100 according to the embodiment uses, as a determination factor, a difference between a job type that is easy to answer a phone call (such as an outside sales job) and a job type that is difficult to answer a phone call (such as a production job in a factory), Working hours can be used as a judgment factor. Thereby, the determination apparatus 100 can improve the accuracy of determination.

  Moreover, the acquisition part 131 acquires the information regarding the communication condition in the information terminal installed in the user terminal 10 and a user's home. The determination unit 132 determines the user's call possibility based on the information related to the communication status.

  As described above, the determination apparatus 100 according to the embodiment estimates the context of the user such as the user being at home by acquiring the communication status between the information devices such as the user terminal 10 and reflects the estimated information. Can be made. Thereby, the determination apparatus 100 can improve the accuracy of determination.

  In addition, the determination apparatus 100 according to the embodiment determines the determination unit 134 that determines the mode of calling for the user based on the user's call possibility determined by the determination unit 132 and the person who calls the user. A transmission unit 135 that transmits the mode of the call determined by the unit 134.

  As described above, the determination apparatus 100 according to the embodiment may transmit a call form reflecting the determination result to a caller or the like. Thereby, the determination apparatus 100 can provide useful information to a business operator that provides a service whose efficiency varies depending on whether or not to respond to a call.

  The embodiment of the present application has been described in detail with reference to the drawings. However, this is an exemplification, and various modifications and improvements are made based on the knowledge of those skilled in the art including the aspects described in the column of the disclosure of the invention. The present invention can be implemented in other forms.

  In addition, the “section (module, unit)” described above can be read as “means” or “circuit”. For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 Judgment processing system 10 User terminal 30 Service server 50 Caller apparatus 100 Judgment apparatus 110 Communication part 120 Storage part 121 Usage condition storage part 122 Attribute table 123A Sensor table 123B Service table 124 Definition table 125 Model storage part 126 Learning data table 127 Model table 129 Calling mode storage unit 130 Control unit 131 Acquisition unit 132 Determination unit 133 Generation unit 134 Determination unit 135 Transmission unit

Claims (25)

An acquisition unit that acquires information about a user's behavior that is detected through the terminal carried by the user, which is information about a usage status of the terminal used by the user;
Judgment for determining the call possibility of the user at a predetermined timing based on the relationship between the usage status acquired by the acquisition unit and the call possibility that the user is likely to make a call to the call And
A determination apparatus comprising: An acquisition unit for acquiring the usage status of the terminal used by the user;
Judgment for determining the call possibility of the user at a predetermined timing based on the relationship between the usage status acquired by the acquisition unit and the call possibility that the user is likely to make a call to the call And
A model corresponding to each user by learning the relationship between the usage status acquired by the acquisition unit and the result information indicating whether or not each user has made a call to the call to each user And a generation unit that generates a model for calculating a score for determining the call possibility of each user.
The determination unit
Using the model corresponding to each user generated by the generation unit, the individual call possibility corresponding to the information indicating the individual status in which each user uses the terminal among the usage status acquired by the acquisition unit Determine
A determination apparatus characterized by that. By learning the relationship between the usage status acquired by the acquisition unit and the result information indicating whether or not the user has made a call with respect to the call to the user, the call possibility of the user can be increased. A generating unit for generating a model for calculating a score to be determined ;
Further comprising
The determination unit
Using the model generated by the generation unit, determine the call possibility of the user,
The determination apparatus according to claim 1, wherein: The determination unit
Based on the day of the predetermined timing, the call possibility of the user is determined.
The determination apparatus according to any one of claims 1 to 3, wherein The determination unit
Based on the time zone of the predetermined timing, the call possibility of the user is determined.
The determination apparatus according to claim 1, wherein: The acquisition unit
As the usage status, acquire the location information of the terminal,
The determination unit
Determining the call possibility of the user based on the score corresponding to the location information;
The determination apparatus according to claim 1, wherein: The determination unit
Based on whether the location information acquired by the acquisition unit is location information indicating the location of the user's home, the call possibility of the user is determined.
The determination apparatus according to claim 6. The acquisition unit
Obtaining time information estimated to elapse when the user moves from the position indicated by the position information to the user's home;
The determination unit
Based on the score corresponding to the time information, the call possibility of the user at the predetermined timing is determined.
The determination apparatus according to claim 7. The acquisition unit
As the usage status, obtain operation information indicating the physical operation of the user for the terminal,
The determination unit
Determining the call possibility of the user based on the score corresponding to the motion information;
The determination apparatus according to claim 1, wherein: The acquisition unit
As the usage status, obtain operation information indicating whether or not the user is operating the terminal,
The determination unit
Determining the call possibility of the user based on the score corresponding to the operation information;
The determination apparatus according to claim 1, wherein: The acquisition unit
As the usage status, the acceleration in the terminal or the moving speed of the terminal is acquired,
The determination unit
Based on a score corresponding to the acceleration or moving speed, the call possibility of the user is determined.
The determination apparatus according to claim 1, wherein: The acquisition unit
As the usage status, obtain illuminance information around the terminal,
The determination unit
Based on the score corresponding to the illuminance information, the call possibility of the user is determined.
The determination apparatus according to claim 1, wherein The acquisition unit
As the usage status, obtain connection information indicating whether an audio output device is connected to the terminal;
The determination unit
Determining a call possibility of the user based on a score corresponding to the connection information;
The determination apparatus according to claim 1, wherein The acquisition unit
As the usage status, obtain application operation information that is information related to application operation on the terminal,
The determination unit
Based on a score corresponding to the application operation information, the call possibility of the user is determined.
The determination apparatus according to claim 1, wherein The acquisition unit
Acquire identification information for identifying the app that the user is operating, or app category,
The determination unit
Based on the identification information for identifying the application or the category of the application, the call possibility of the user is determined.
The determination apparatus according to claim 14. The acquisition unit
As the usage status, obtaining usage information regarding the service used by the user via the terminal;
The determination apparatus according to claim 1, wherein: The acquisition unit
In the use of services related to purchasing, obtain information on the delivery schedule specified by the user,
The determination unit
Determining a call possibility of the user based on a score corresponding to information on the delivery schedule;
The determination apparatus according to claim 16. The acquisition unit
In the use of a service related to reservation of at least one of transportation, travel, eating and drinking facilities, or accommodation facilities, obtain information on the reservation schedule reserved by the user,
The determination unit
Based on a score corresponding to information related to the reservation schedule, the call possibility of the user is determined.
The determination apparatus according to claim 16 or 17, characterized in that: The acquisition unit
Among the attribute information registered by the user in the service, obtain information on the job type or working hours of the user,
The determination unit
Based on the score corresponding to the user's occupation or working time, the call possibility of the user is determined.
The determination apparatus according to any one of claims 16 to 18, wherein The acquisition unit
Obtain information regarding the communication status of the terminal and information equipment installed at the user's home,
The determination unit
Determining a call possibility of the user based on a score corresponding to the information on the communication status;
The determination apparatus according to claim 1, wherein A determination unit that determines a mode of call for the user based on the call possibility of the user determined by the determination unit;
A transmission unit for transmitting a call mode determined by the determination unit to a person who calls the user;
The determination apparatus according to claim 1, further comprising: A determination method executed by a computer,
An acquisition step for acquiring information on a user's behavior that is detected through the terminal carried by the user, which is information on a usage status of the terminal used by the user;
Judgment to determine the call possibility of the user at a predetermined timing based on the relationship between the usage situation acquired by the acquisition step and the call possibility that the user is likely to make a call to the call Process,
The determination method characterized by including. An acquisition procedure for acquiring information on a user's behavior that is detected through the terminal carried by the user, which is information on a usage status of the terminal used by the user;
Judgment to determine the call possibility of the user at a predetermined timing based on the relationship between the usage situation acquired by the acquisition procedure and the call possibility that is a possibility that the user can make a call to the call. Procedure and
The determination program characterized by causing a computer to execute. A determination method executed by a computer,
An acquisition step of acquiring the usage status of the terminal used by the user;
Judgment to determine the call possibility of the user at a predetermined timing based on the relationship between the usage situation acquired by the acquisition step and the call possibility that the user is likely to make a call to the call Process,
A model corresponding to each user by learning the relationship between the usage status acquired by the acquisition step and the result information indicating whether or not each user has made a call to the call to each user. A generation step of generating a model for calculating a score for determining the call possibility of each user,
The determination step includes
Using the model corresponding to each user generated by the generating step, individual call possibility corresponding to information indicating the individual status of each user using the terminal among the usage status acquired by the acquiring step Determine
The determination method characterized by this. An acquisition procedure for acquiring the usage status of the terminal used by the user;
Judgment to determine the call possibility of the user at a predetermined timing based on the relationship between the usage situation acquired by the acquisition procedure and the call possibility that is a possibility that the user can make a call to the call. Procedure and
A model corresponding to each user by learning the relationship between the usage status acquired by the acquisition procedure and the result information indicating whether or not each user has made a call to the call to each user. And causing the computer to execute a generation procedure for generating a model for calculating a score for determining the call possibility of each user,
The determination procedure is as follows:
Using the model corresponding to each user generated by the generation procedure, the individual call possibility corresponding to information indicating the individual status in which each user uses the terminal among the usage status acquired by the acquisition procedure Determine
Judgment program characterized by that.

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