JP7293171B2 - Information processing device, information processing method and information processing program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

Conventionally, techniques for estimating user information based on various types of information are known. As an example of such a technique, there is a technique for estimating bases such as a user's home or workplace based on position information acquired by a terminal device used by the user (see, for example, Patent Document 1).

WO2011/102541

However, the conventional technology described above has room for improvement in estimating user information with high accuracy. For example, in the conventional technology, since the user's home or workplace is estimated according to the length of stay based on location information, there is a risk that the user's location cannot be estimated with high accuracy for a user who behaves irregularly. .

The present application has been made in view of the above, and aims to provide an information processing apparatus, an information processing method, and an information processing program capable of estimating user information with high accuracy.

An information processing apparatus according to the present application includes an acquisition unit that acquires behavior information indicating behavior of a user, a detection unit that detects a specific event that affects the behavior of the user, and an event detected by the detection unit. an estimating unit for estimating the user's context based on the behavior information of the event period related to the event.

According to one aspect of the embodiment, there is an effect that the information of the user can be estimated with high accuracy.

FIG. 1 is a diagram showing an overview of an information processing method according to an embodiment. FIG. 2 is a diagram showing the configuration of the information processing system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of a user terminal according to the embodiment; FIG. 4 is a diagram illustrating a configuration example of an information processing apparatus according to the embodiment; FIG. 5 is a diagram showing an example of user information. FIG. 6 is a diagram showing an example of action information. FIG. 7 is an explanatory diagram for explaining the estimation processing of the estimation unit. FIG. 8 is a flowchart illustrating a processing procedure of processing executed by the information processing apparatus according to the embodiment; FIG. 9 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus according to the embodiment.

Hereinafter, modes for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Also, in each of the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

(embodiment)
[Outline of information processing]
First, an outline of an information processing method according to an embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an overview of an information processing method according to an embodiment.

FIG. 1 shows a terminal device 100 owned by a user and an information processing device 1 . An information processing method according to the embodiment is executed by the information processing device 1 . Specifically, in the information processing method, the user's context is estimated based on the user's behavior during the period when a specific event occurred.

In addition, in FIG. 1, as an example of the information processing method, a case of estimating the user's home and workplace from the user's position information will be described.

Here, in the conventional technology, when estimating the home and workplace from the user's location information, the home and workplace are estimated according to the length of time the user stays. Alternatively, since most users generally stay at work during the daytime and stay at home during the nighttime, it is possible to estimate home and work based on the time zone of the location information. There is also a conventional technology to

However, in the above-described conventional technology, for example, users such as students whose lifestyles are irregular and location information tends to vary, and users who lead a day-and-night lifestyle, that is, stay at home during the day and work at the office at night. There was a risk that the accuracy of estimating home and work would be reduced for users who stay in

Therefore, in the information processing method according to the embodiment, the user's context (home and workplace) is estimated based on behavior information during a period when a specific event affecting the user's behavior is occurring.

In FIG. 1, as a specific event, a stay-at-home request issued to prevent a virus pandemic will be described as an example.

As shown in FIG. 1, the information processing device 1 first acquires position information from each user via the terminal device 100 (step S1). The information processing device 1 periodically acquires and accumulates position information.

In FIG. 1, location information is used as an example of behavior information indicating user behavior. Any information may be used as long as it is information.

Subsequently, the information processing device 1 detects a specific event that affects the behavior of the user (step S2). In the example shown in FIG. 1, a stay-at-home request issued to prevent a virus pandemic is detected as a specific event. Note that such a specific event can be detected based on information that can be acquired from an external device such as a server device that distributes news, for example.

Subsequently, the information processing device 1 estimates the user's context based on the action information of the event period related to the specific event (step S3). For example, the information processing apparatus 1 assumes the period during which a request to refrain from going out is issued as an event period, and estimates the user's home and workplace from position information during the event period.

For example, the information processing apparatus 1 compares the location information during the event period with the location information during the period other than the event period, and estimates that the location where the location information increased during the event period is the home. That is, the information processing apparatus 1 estimates the home as the user's context by noting that the stay time at the user's home increases due to the refraining from going out request.

Although the details will be described later, the information processing apparatus 1 can determine whether the context estimated based on the action information during the period other than the event period is correct based on the action information during the event period. In other words, the information processing apparatus 1 determines whether the user's home estimated from the position information during the normal period other than the refraining from going out period is correct based on the position information during the refraining from going out period.

As described above, according to the information processing method according to the embodiment, user information can be estimated with high accuracy by estimating the user's context by focusing on the fact that the user performs a specific action due to a specific event. can be done.

Note that FIG. 1 shows a case in which the user's home or workplace is estimated based on location information as the context, but another example of context estimation is to estimate whether the user owns a private car. There is an example to

Specifically, the information processing apparatus 1 acquires, as the behavior information, search query information, position information, and information on the usage status of transfer applications and the like. Then, the information processing apparatus 1 estimates whether or not the user owns a private car, which is the context of the user, based on the behavior information.

For example, the information processing apparatus 1 assumes that during the normal period (period other than the event period), the action information shows that the user frequently travels by train and does not own a private car as a context. Then, when the information processing apparatus 1 obtains behavior information indicating that movement by train is reduced and movement by car is increased during an event period in which a virus pandemic is occurring, the information processing device 1 can obtain behavior information (moving on a roadway at a predetermined speed or higher, are not scattered at the station, etc.), the user owns a private car.

In this way, the information processing device 1 can estimate various contexts from the comparison of the behavior information in the event period and the period other than the event period.

[Information processing system]
Next, an information processing system including the information processing apparatus 1 will be described with reference to FIG. FIG. 2 is a diagram showing the configuration of the information processing system S according to the embodiment. As shown in FIG. 2 , an information processing system S according to the embodiment includes an information processing device 1 and a plurality of user terminals 100 . These various devices are communicably connected by wire or wirelessly via a predetermined network N such as the Internet.

The information processing device 1 is an information processing device that executes the information processing described above, and is realized by, for example, a server device, a cloud system, or the like. For example, the information processing device 1 acquires behavior information from the user terminal 100, and uses the acquired behavior information to perform a process of estimating a user's context, a process of providing content using the context, and the like.

A user terminal 100 is a terminal device used by a user. The user terminal 100 is realized by, for example, a smart phone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like. In addition, below, the user terminal 100 may be described as the terminal device 100. FIG.

The user terminal 100 executes a process of detecting behavior information with its own sensor and a process of transmitting the behavior information to the information processing device 1 .

[Configuration of user terminal]
Next, the configuration of the user terminal 100 according to the embodiment will be described using FIG. FIG. 3 is a diagram showing a configuration example of the user terminal 100 according to the embodiment. As shown in FIG. 3 , the user terminal 100 has a communication section 200 , a control section 300 , a storage section 400 , an input section 500 and a display section 600 .

The input unit 500 receives various operations from the user. For example, the input unit 500 is configured with a keyboard, mouse, and the like. The display unit 600 displays various information. For example, the display unit 600 is composed of a liquid crystal display or the like.

The communication unit 200 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 200 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the information processing device 1 .

The storage unit 400 is implemented by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or an optical disk.

(control part)
The control unit 300 is a controller, and various programs stored in a storage device inside the terminal device 100 are executed by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like, using the RAM as a work area. It is realized by being executed. Also, the control unit 300 is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 3, the control unit 300 has an acquisition unit 310 and a transmission unit 320, and realizes or executes information processing functions and actions described below.

(acquisition part)
Acquisition unit 310 acquires behavior information related to user behavior. For example, the behavior information includes information about the user's actual behavior and information about the user's behavior on the network.

Information about the user's actual behavior is, for example, location information (or changes in location information) indicating the user's current location. The acquisition unit 310 acquires, as position information, for example, a position measured based on received signals from GPS (Global Positioning System) satellites or a position using beacons placed around the user.

In addition, the information on the user's behavior on the network is, for example, information on search behavior in a predetermined search service (search query, etc.), information on purchasing behavior in an electronic commerce service (purchased goods, searched goods, etc.) ), and information on the response behavior of the user to the distributed content (viewing of videos, viewing of advertisements, opening of e-mails, etc.).

(Transmitter)
The transmission unit 320 transmits the behavior information acquired by the acquisition unit 310 to the information processing device 1 . The transmission timing of the action information by the transmission unit 320 may be arbitrary. For example, the transmission unit 320 may transmit the behavior information to the information processing device 1 each time it acquires the behavior information, or may collectively transmit the behavior information to the information processing device 1 at regular intervals (for example, every day). .

[Configuration of information processing device]
Next, the configuration of the information processing apparatus 1 according to the embodiment will be described using FIG. FIG. 4 is a diagram showing a configuration example of the information processing device 1 according to the embodiment. As shown in FIG. 4 , the information processing device 1 has a communication section 2 , a control section 3 and a storage section 4 .

The communication unit 2 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 2 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the user terminal 100 .

The storage unit 4 is implemented 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 disc. As shown in FIG. 4 , the storage unit 4 stores user information 40 and action information 41 .

User information 40 is information about the user. FIG. 5 is a diagram showing an example of user information 40. As shown in FIG. As shown in FIG. 5, the user information 40 includes items such as "user ID" and "context information".

“User ID” is identification information that identifies a user. The “context information” is information indicating the user's context, which is estimated by the estimation unit 32 described later.

Here, the context is information indicating the user's situation and the user's environment. Specifically, the context includes the user's geographic attributes (home location, workplace location, location of frequently used facilities, etc.), demographic attributes (age, income, occupation, etc.), and psychographic attributes. Attributes (values, lifestyle, personality, preferences, etc.) are included.

The action information 41 is action information regarding actions of each user acquired from a plurality of user terminals 100 . FIG. 6 is a diagram showing an example of the action information 41. As shown in FIG. As shown in FIG. 6, the action information 41 includes items such as "user ID" and "action information."

“User ID” is identification information that identifies a user. “Action information” is information that includes various types of action information that the acquisition unit 30 has acquired from the user terminal 100 .

For example, "action information" includes action information acquired from the user terminal 100 described above. Specifically, the behavior information includes information about the user's actual behavior and information about the user's behavior on the network.

(control part)
The control unit 3 is a controller, and various programs stored in a storage device inside the information processing apparatus 1 are stored in the RAM by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. It is realized by executing as Also, the control unit 3 is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 4, the control unit 3 includes an acquisition unit 30, a detection unit 31, an estimation unit 32, and a provision unit 33, and implements or executes information processing functions and actions described below. .

(acquisition unit)
The acquisition unit 30 acquires behavior information regarding user behavior. For example, the acquisition unit 30 acquires behavior information acquired by the acquisition unit 310 of the user terminal 100 . Further, the acquisition unit 30 may acquire behavior information in a service, that is, information about a user's behavior on a network, from a server device that provides a predetermined service.

(Detection unit)
The detection unit 31 detects specific events that affect user behavior. The detection unit 31 detects, for example, naturally occurring disasters (earthquakes, typhoons, large-scale fires, landslides, tsunamis, infectious disease pandemics, etc.) and artificially occurring disasters (air pollution, etc.) as specific events. Pollution, traffic accidents, war, etc.).

Further, the detection unit 31 may detect the above-described disaster countermeasures (a request to refrain from going out, a request for evacuation, etc.) as a specific event. The detection unit 31 may also detect various trends (so-called booms) such as movies, dramas, music, and fashion as specific events.

The above-described disasters, countermeasures associated with disasters, and various trends make it easier for a plurality of users to take the same actions in terms of actual actions of users and actions on networks (search actions and purchasing actions).

In other words, the detection unit 31 detects, as a specific event, an event that makes it easier for the user to take the same action. Note that the detection unit 31 can detect a specific event based on information acquired from a server device that provides various news, a server device that provides social network services, or the like.

The detection unit 31 also detects an event period related to the detected specific event. For example, the detection unit 31 detects a predetermined period before and after the timing at which a specific event occurs as an event period. Further, the detection unit 31 may detect, for example, a period specified by an external device or the like regarding a specific event as the event period. Further, the detection unit 31 may predict the event period based on information acquired from an external device.

(Estimation part)
The estimation unit 32 estimates the user's context based on the behavior information acquired by the acquisition unit 30 . For example, the estimation unit 32 estimates the user's situation and the user's environment as the context. Specifically, the estimation unit 32 uses the user's geographic attributes (home location, workplace location, location of frequently used facilities, etc.) and demographic attributes (age, income, occupation, etc.) as the context. ) and psychographic attributes (values, lifestyle, personality, preferences, etc.).

For example, the estimation unit 32 estimates the base such as the user's home or workplace based on the history of position information during the event period of a request to refrain from going out, which is a specific event. Specifically, the estimating unit 32 estimates the position with the longest staying time as the home, the position with the second longest staying time as the workplace, and the position with the third longest staying time in the history of the position information. are assumed to be lifeline-related locations (supermarkets, convenience stores, etc.).

In addition, the estimation unit 32 determines whether the user's age, gender, sensitivity to fashion, etc. is based on the user's search behavior during the event period of a specific event, which is a predetermined trend (for example, singer A's B song is a big hit). Estimate the attributes of Specifically, the estimation unit 32, in the event period, when the user specifies a keyword related to singer A or song B as a search query and selects information on singer A or song B from the search results, It can be assumed that such users are in their twenties and fashion conscious.

In addition, the estimation unit 32 determines that the user is a high-income person ( yearly income is equal to or greater than a predetermined value).

Also, the estimation unit 32 can, for example, determine the correctness of the context estimated based on the behavior information during a period other than the event period (normal period), based on the behavior information during the event period.

Specifically, in a context estimated based on behavior information during a period other than the event period, the estimation unit 32 determines the difference between the first information during the event period of the context and the second information during the period other than the event period of the context. Based on, the right or wrong of the context is determined. Here, this point will be described with reference to FIG.

FIG. 7 is a diagram showing estimation processing by the estimation unit 32. As shown in FIG. In addition, in FIG. 7, a request for refraining from going out will be described as an example of a specific event. FIG. 7 shows a graph relating to the time spent at home and at work, which is the user's context. Note that the "home" and "workplace" contexts shown in FIG. 7 are estimated based on the position information during a period other than the event period (normal period).

In the graph of FIG. 7, the horizontal axis indicates the difference in time spent at home, and the vertical axis indicates the difference in time spent at work. Specifically, the difference between the time spent at home is the time spent at home based on location information during the event period (an example of first information) and the time spent at home based on location information for a period other than the event period (an example of second information). ). More specifically, the difference in time spent at home shown in FIG. 7 is a value obtained by normalizing the amount of change (difference) from the time spent at home, which is the second information, to the time spent at home, which is the first information, according to a predetermined condition. be.

In addition, the difference in time spent at work is the time spent at work based on location information during the event period (an example of first information) and the time spent at work based on location information during periods other than the event period (an example of second information). Show difference. More specifically, the difference in time spent at work shown in FIG. 7 is a value obtained by normalizing the amount of change (difference) from the time spent at work, which is the second information, to the time spent at work, which is first information, according to a predetermined condition. be.

When the value is 0, it indicates that there is no change between the first information and the second information. It is larger than normal, and the larger the value is on the negative side, the shorter the stay at home (or workplace) during refraining from going out.

Here, in general, during the self-restraint period, there is a tendency that unnecessary and non-urgent outings such as travel decrease and the time spent at home increases. In addition, during the period of refraining from going out, there is a tendency for companies to introduce telecommuting and reduce (or not change) the time spent at the workplace.

However, in the graph of FIG. 7, there are a certain number of users who spend less time at home and more time at work during the self-restraint period. In other words, in the graph of FIG. 7, there are users who behave in a completely opposite manner to general users' behavior even during the self-restraint period.

Here, when the inventors confirmed the home and workplace of the user who was presumed to take the opposite behavior, it was found that the estimated context was different from the actual context. In other words, it turned out that the estimated context of home is actually the workplace, and the estimated context of work is home. That is, there was an error in the estimated context based on the position information during the period other than the event period.

Focusing on this point, the estimating unit 32 determines that the context, which is the result of estimation, is erroneous when the user takes an action that is opposite to the action that the user tends to take in a specific event. Specifically, when the difference between the first information and the second information satisfies a predetermined threshold condition, the estimating unit 32 determines that the estimation result of the context estimated based on the action information during the period other than the event period is erroneous. I judge.

In the example shown in FIG. 7, the estimating unit 32 determines that for users whose difference in time spent at home is less than the first threshold TH and/or whose difference in time spent at work is equal to or greater than the second threshold TH, is determined to be an error.

Then, when determining that the estimation result is incorrect, the estimation unit 32 corrects the context based on the difference described above. For example, the estimating unit 32 performs a correction to replace the home and workplace contexts based on the difference in time spent at home and the difference in time spent at work. This can improve the accuracy of the final estimation result (context after correction).

Note that the estimating unit 32 is not limited to judging whether the context is right or wrong based on the difference between the first information and the second information. Whether the second context is right or wrong may be determined based on the result of comparison with the second context estimated from the behavior information in the period.

Specifically, the estimation unit 32 determines that the second context is correct when the first context and the second context are the same, and determines that the second context is correct when the first context and the second context are different. is an error. In such a case, the estimation unit 32 corrects the second context to the first context.

Note that the estimation unit 32 may omit the second context estimation process and perform only the first context estimation process.

Further, FIG. 7 shows a case where the correctness of the context estimated based on the action information during the period other than the event period is determined. The context may be estimated directly from the comparison result of the behavior information in the event period and the period other than the event period.

Specifically, the estimating unit 32 estimates the context also based on the difference between the action information of the event period and the action information of the event period. More specifically, the estimating unit 32 determines that, at a specific position (place, area), the length of stay during the event period, which is the self-restraint period, has increased more than the length of stay during periods other than the event period (highest rate of increase). ), presumed at home.

(providing department)
The providing unit 33 provides content to the user based on the context estimated by the estimating unit 32 . Specifically, the providing unit 33 provides the content determined by the estimating unit 32 based on the content that is the estimated result after correction.

As for the content providing method by the providing unit 33, for example, the providing unit 33 may voluntarily provide the content to the user by a push notification, or provide the content in response to the user's action, that is, passively provide the content. may provide.

[Processing procedure]
Next, a procedure of processing executed by the information processing apparatus 1 according to the embodiment will be described with reference to FIG. FIG. 8 is a flowchart showing the procedure of processing executed by the information processing apparatus 1 according to the embodiment.

As shown in FIG. 8, first, the acquisition unit 30 acquires behavior information about user behavior from the user terminal 100 (step S101).

Subsequently, the estimating unit 32 estimates a context based on behavior information during a period other than the event period (step S102).

Subsequently, the estimation unit 32 generates first information in the event period of the estimated context and second information in a period other than the event period of the context (step S103).

Subsequently, the estimation unit 32 calculates the difference between the first information and the second information (step S104).

Subsequently, the estimation unit 32 determines whether the difference satisfies a predetermined threshold condition (step S105).

If the difference satisfies the threshold condition (step S105: Yes), the estimation unit 32 corrects the context estimated in step S102 (step S106), and ends the process.

On the other hand, if the difference does not satisfy the threshold condition (step S105: No), the estimation unit 32 ends the process. That is, the estimation unit 32 uses the context estimated in step S102 as the final estimation result.

〔effect〕
As described above, the information processing device 1 according to the embodiment includes the acquisition unit 30 , the detection unit 31 and the estimation unit 32 . The acquisition unit 30 acquires behavior information indicating behavior of the user. The detection unit 31 detects specific events that affect user behavior. The estimating unit 32 estimates the user's context based on the behavior information of the event period related to the specific event detected by the detecting unit 31 .

Thereby, the user's information (context) can be estimated with high accuracy.

The acquisition unit 30 also acquires position information as action information. The estimation unit 32 estimates the location of the user as the context.

As a result, the user's location can be estimated with high accuracy as the user's context.

Also, the user's location includes at least home and work.

As a result, home and work can be estimated with high accuracy as the user's context.

In addition, the estimation unit 32 estimates the context based on the result of comparison between the action information during the event period and the action information during periods other than the event period.

Thereby, the user's context can be estimated with high accuracy.

Also, the estimation unit 32 determines whether the second context estimated based on the behavior information in the period before the event period is correct based on the first context estimated based on the behavior information in the event period.

As a result, it is possible to determine with high accuracy whether the estimation result of the second context is correct.

Further, the estimation unit 32, in the context estimated based on the behavior information during the period other than the event period, based on the difference between the first information during the event period of the context and the second information during the period other than the event period of the context, Determine whether the context is correct or not.

As a result, it is possible to determine with high accuracy whether the context estimated based on the behavior information during the period other than the event period is correct.

Further, when the difference between the first information and the second information satisfies a predetermined threshold condition, the estimation unit 32 determines that the estimated context estimation result is erroneous, and estimates the context estimation result based on the difference. to correct.

This makes it possible to improve the accuracy of the corrected context.

Moreover, the information processing apparatus 1 according to the embodiment further includes a providing unit 33 . The providing unit 33 provides content to the user based on the context estimated by the estimating unit 32 .

This makes it possible to provide more appropriate content that matches the user's context.

〔program〕
Further, the information processing apparatus 1 according to the above-described embodiments is implemented by a computer 1000 configured as shown in FIG. 9, for example. FIG. 9 is a hardware configuration diagram showing an example of a computer 1000 that implements the functions of the information processing apparatus 1 according to the embodiment. Computer 1000 has 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 programs stored in the ROM 1300 or HDD 1400 and controls each section. 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 programs executed by the CPU 1100, data used by the programs, and the like. Communication interface 1500 receives data from other devices via a network (for example, network N), sends the data to CPU 1100, and transmits data generated by CPU 1100 to other devices via network N.

The CPU 1100 controls, via an input/output interface 1600, input/output devices such as output devices such as displays and printers, and input devices such as keyboards and mice. CPU 1100 acquires data from an input device via input/output interface 1600 . CPU 1100 also outputs the generated data to an output device via input/output interface 1600 .

Media interface 1700 reads programs or data stored in recording medium 1800 and provides them to CPU 1100 via RAM 1200 . CPU 1100 loads such a program from recording medium 1800 onto RAM 1200 via 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 a PD (Phase change rewritable disc), 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 information processing apparatus 1 according to the embodiment, the CPU 1100 of the computer 1000 implements the functions of the control unit 3 by executing programs loaded on the RAM 1200 . Data in the storage unit 4 is stored in the HDD 1400 . CPU 1100 of computer 1000 reads and executes these programs from recording medium 1800, but as another example, these programs may be acquired via network N from another device.

As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to carry out the invention in other forms with modifications.

〔others〕
Further, among the processes described in the above embodiments, all or part of the processes described as being automatically performed can be manually performed, or the processes described as being performed manually can be performed manually. All or part of this can also be done automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

Further, each processing described in the above-described embodiments can be appropriately combined within a range that does not contradict the content of the processing.

Also, the "section, module, unit" described above can be read as "means" or "circuit". For example, the acquisition unit 30 can be read as acquisition means or an acquisition circuit.

1 information processing device 2, 200 communication unit 3, 300 control unit 4, 400 storage unit 30, 310 acquisition unit 31 detection unit 32 estimation unit 33 provision unit 100 terminal device (user terminal)
320 transmission unit 500 input unit 600 display unit S information processing system

Claims (8)

an acquisition unit that acquires behavior information indicating user behavior;
a detection unit that detects a specific event that temporarily occurs and that is a specific event that affects the behavior of the user;
an estimating unit for estimating the user's context based on the behavior information of an event period related to the event detected by the detecting unit ;
with
The estimation unit
The first context estimated based on the behavior information during the event period and the second context estimated based on the behavior information during the period prior to the event period, and the comparison result of the second context. judging right or wrong
An information processing device characterized by: The acquisition unit
Acquiring location information as the action information,
The estimation unit
The information processing apparatus according to claim 1, wherein the location of the user is estimated as the context. 3. The information processing apparatus according to claim 2, wherein the user's bases include at least a home and a workplace. The estimation unit
In the context estimated based on the behavior information during a period other than the event period, the difference between the first information during the event period of the context and the second information during the period other than the event period of the context 2. The information processing apparatus according to claim 1 , wherein the right or wrong of the context is determined based on. The estimation unit
If the difference between the first information and the second information satisfies a predetermined threshold condition, it is determined that the estimated context estimation result is erroneous, and the context estimation result is corrected based on the difference. The information processing apparatus according to claim 4 , characterized by: The information processing apparatus according to any one of claims 1 to 5 , further comprising a providing unit that provides content to the user based on the context estimated by the estimating unit. An information processing method executed by an information processing device,
an acquisition step of acquiring behavior information indicating user behavior;
a detection step of detecting a specific event that affects the behavior of the user and that occurs temporarily;
an estimating step of estimating the user's context based on the behavioral information during an event period to which the event detected by the detecting step relates ;
including
The estimation step includes
The first context estimated based on the behavior information during the event period and the second context estimated based on the behavior information during the period prior to the event period, and the comparison result of the second context. judging right or wrong
An information processing method characterized by: an acquisition procedure for acquiring behavior information indicating user behavior;
a detection procedure for detecting a specific event, which is a specific event that affects the behavior of the user and that occurs temporarily;
an estimation procedure for estimating the user's context based on the behavioral information during an event period to which the event detected by the detection procedure relates ;
on the computer , and
The estimation procedure includes:
The first context estimated based on the behavior information during the event period and the second context estimated based on the behavior information during the period prior to the event period, and the comparison result of the second context. judging right or wrong
An information processing program characterized by

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