JP2017010223A - Information processing device, information processing method and information processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable the detection of an event about the future with high accuracy.SOLUTION: An information processing device relating to the invention includes an acquisition part, and a detection part. The acquisition part acquires past intention information showing an intention about a past action before the present time point, and future intention information showing an intention about a future action during a prescribed period after the present time point, the action corresponding to the past action. The detection part detects an event about the future on the basis of the past intention information and the future intention information acquired by the acquisition part.SELECTED DRAWING: Figure 3

Description

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

  In recent years, techniques for predicting the location of a user are known. For example, in such a technique related to prediction, a location where the user will stay in the future is estimated using information on a position where the user has stayed in the past and information on a scheduler or a search log.

JP 2011-198292 A Japanese Patent Laying-Open No. 2015-26136

  However, with the above-described conventional technology, events related to the future cannot always be detected with high accuracy. For example, in the above-described conventional technology, since the user is only inferring where the user will stay in the future based on the co-occurrence relationship between the position where the user has stayed in the past and the schedule included in the user's personal scheduler. It was not always possible to detect events related to the future with high accuracy. Although the above prior art seems to assume the case of individual users, there is still a problem in terms of the accuracy of detection of events related to the future even when targeting an unspecified number of users.

  The present application has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program capable of detecting an event related to the future with high accuracy.

  The information processing apparatus according to the present application includes past intention information indicating intentions related to past actions from the present time, and future intention information indicating actions corresponding to the past actions and indicating future actions for a predetermined period from the present time. An acquisition unit for acquiring and a detection unit for detecting an event related to the future based on past intention information and future intention information acquired by the acquisition unit are provided.

  According to one aspect of the embodiment, there is an effect that an event related to the future can be detected with high accuracy.

FIG. 1 is an explanatory diagram illustrating an example of detection processing by the information processing system according to the embodiment. FIG. 2 is an explanatory diagram for explaining the detection process. FIG. 3 is a diagram illustrating a configuration example of the information processing apparatus according to the embodiment. FIG. 4 is a diagram illustrating an example of the intention information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of the cumulative information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of the abnormality information storage unit according to the embodiment. FIG. 7 is an explanatory diagram for explaining model adjustment. FIG. 8 is an explanatory diagram for explaining the overall processing flow in the information processing system. FIG. 9 is a diagram illustrating an example of a screen. FIG. 10 is an explanatory diagram for explaining the flow of display processing by the information processing system. FIG. 11 is a flowchart illustrating an information processing procedure performed by the information processing apparatus. FIG. 12 is a hardware configuration diagram illustrating an example of a computer that implements the functions of the information processing apparatus.

  Hereinafter, a mode for carrying out an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as “embodiment”) will be described in detail with reference to the drawings. Note that the information processing apparatus, the information processing method, and the information processing program according to the present application are not limited by this embodiment. Moreover, in the following embodiment, the same code | symbol is attached | subjected to the same site | part and the overlapping description is abbreviate | omitted.

[1. Embodiment)
[1-1. Detection Processing According to Embodiment]
First, an example of detection processing according to the embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram illustrating an example of detection processing by the information processing system 1 according to the embodiment. In the example of FIG. 1, a detection process for detecting an abnormality relating to the future (corresponding to an example of an event) is performed by the information processing apparatus 100.

  As illustrated in FIG. 1, the information processing system 1 includes terminal devices 10 </ b> A to 10 </ b> C, an information providing server 50, and an information processing device 100. The terminal apparatuses 10A to 10C, the information providing server 50, and the information processing apparatus 100 are each connected to a network so that they can communicate with each other by wire or wirelessly. Hereinafter, the terminal devices 10 </ b> A to 10 </ b> C may be collectively referred to as “terminal device 10” when collectively referred to without distinction.

  As an example, the terminal device 10 is an information processing device such as a smartphone, a PC (Personal Computer), a tablet terminal, a mobile phone, or a PDA (Personal Digital Assistant). For example, the terminal device 10 receives and displays various information provided by the information providing server 50 by transmitting various requests to the information providing server 50.

  The information providing server 50 is a Web server that provides an information providing service. For example, in response to a request from the terminal device 10, the information providing server 50 provides the terminal device 10 with route information related to a route such as transfer guidance for transportation or operation information.

  Here, for example, when a sudden bad weather or an event occurs, there are cases where more people gather at the station or the like than in a normal case and are congested. Therefore, the information processing apparatus 100 uses the information transmitted from the terminal apparatus 10 and stored in the information providing server 50 to detect abnormalities related to the future that are different from events related to the past, such as a station being congested compared to a normal case. Execute detection processing to detect. This point will be described in detail with reference to FIG.

  First, the terminal device 10 receives a search operation by a user, and executes a route search from a Web page provided by the information providing server 50 (step S1). Here, the terminal device 10 transmits intention information indicating the intention regarding the user's behavior to the information providing server 50. For example, the terminal device 10 transmits, as intention information, information related to the place where the user is scheduled to go and the date and time to go to the place to the information providing server 50. As an example, the terminal device 10A, as intention information, the location “A station” designated as the arrival place by the user of the terminal device 10A and the date and time “May 25, 2015 17: Route search information including “00” is transmitted to the information providing server 50 on the search date “May 25, 2015, 9:01”. The terminal device 10B searches for route search information including the location “A station” designated as the arrival place by the user of the terminal device 10B and the date and time “May 25, 2015 18:00” designated as the arrival date and time. The information is sent to the information providing server 50 at the date and time “May 25, 2015, 9:02”. The terminal device 10C searches for route search information including the location “A station” designated as the arrival place by the user of the terminal device 10C and the date and time “May 25, 2015, 17:30” designated as the arrival date and time. The information is transmitted to the information providing server 50 at the date and time “May 25, 2015, 9:03”. Thereby, the information providing server 50 receives the intention information from the terminal device 10. And the information provision server 50 stores the intention information received from the terminal device 10 in a memory | storage part (step S2).

  Subsequently, the information processing apparatus 100 includes past intention information indicating intentions related to past actions from the present time, future intention information indicating actions corresponding to the past actions and indicating future actions for a predetermined period from the present time, Is acquired (step S3). For example, the information processing apparatus 100 acquires, from the information providing server 50, intention information indicating intentions related to past actions from the present time among the intention information as past intention information. As an example, if the current time is “May 25, 2015, 10:00”, the information processing apparatus 100 designates the place “A station” as the arrival place as the past intention information, and the date “ Route search information that specified "May 18, 2015 17:00" as the arrival date and time is acquired. Further, the information processing apparatus 100 acquires, from the information providing server 50, as future intention information, intention information indicating an action related to the past action and indicating a future action for a predetermined period from the present time. To do. As an example, if the current time is “May 25, 2015, 10:00”, the information processing apparatus 100 designates the location “A station” as the arrival place as the future intention information, and the date “ Route search information that specifies “25 May 2015, 17:00” as the arrival date and time is acquired.

  And the information processing apparatus 100 detects the abnormality regarding the future based on the acquired past intention information and future intention information (step S4). Specifically, the information processing apparatus 100 includes the future intention information in which the intention is shown in the first period past from the present time, and a period corresponding to the first period and the second period past the first period. Anomalies related to the future are detected by comparing with past intention information in which intentions are indicated. For example, the information processing apparatus 100 detects an abnormality related to the future by comparing the accumulation of future intention information in which intention is indicated in the first period with the accumulation of past intention information in which intention is indicated in the second period. This point will be described with reference to FIG.

  FIG. 2 is an explanatory diagram for explaining the detection process. In FIG. 2, the vertical axis of the graph indicates the cumulative number of route searches that designate “A station” as an arrival station. The horizontal axis of the graph indicates time. In the example of FIG. 2, the current time is “May 25, 2015, 10:00”. The first period is “May 25, 2015, 0: 00-10: 00”. The second period is “May 18, 2015, 0: 00-10: 00”. A graph L1 illustrated in FIG. 2 indicates the cumulative number of route searches in which the user designates “A station” as an arrival station during the period “May 18, 2015, 0:00 to 10:00”. The graph L2 indicates the cumulative number of route searches in which the user designates “A station” as an arrival station during the period “May 25, 2015, 0:00 to 10:00”. In this case, the information processing apparatus 100 compares the difference between the graph L1 and the graph L2 and detects an abnormality related to the future that is different from an event related to the past. Here, the cumulative number at the time point “May 18, 2015 10:00” of the graph L1 is “4000”. On the other hand, the cumulative number in the graph “L2” “May 25, 2015, 10:00” is “8000”. For this reason, the information processing apparatus 100 has twice the cumulative number of graphs L2 as compared to the graph L1, which is the cumulative number of the same time period on the past day from the graph L2, and the arrival date and time is “2015”. Since there are many route searches with a specified time of "May 25, 17: 00-18: 00", the future is "May 25, 2015, which is a future than" May 25, 2015 10:00 " Anomalies related to the future such as “A station” is crowded between 17:00 and 18:00 are detected.

  As described above, the information processing apparatus 100 according to the embodiment indicates past intention information indicating an intention regarding a past action from the present time, and an action corresponding to the past action and indicating an intention regarding a future action for a predetermined period from the present time. Get future intention information. Further, the information processing apparatus 100 detects an event related to the future based on the acquired past intention information and future intention information.

  Thereby, since the information processing apparatus 100 detects the event about the future using the past intention information indicating the past action corresponding to the future action, it can detect the abnormality about the future with high accuracy.

  Further, the information processing apparatus 100 indicates the future intention information in which the intention is indicated in the first period past from the present time, and the intention corresponding to the first period and in the second period before the first period. Compared with past intention information, events related to the future are detected.

  As a result, the information processing apparatus 100 can compare the difference in intention information between the first period in the past from the current time and the second period corresponding to the first period. can do. For example, the information processing apparatus 100 can compare under the same conditions such as the day of the week and the time zone, and can detect an abnormality related to the future with high accuracy. As an example, the information processing apparatus 100 is highly likely that “A station” is congested as an event related to the future when the number of route searches having “A station” as an arrival station is larger than the corresponding period in the past. It can be detected with accuracy. In addition, the information processing apparatus 100 determines the future date and time when “A station” is crowded with high accuracy based on the arrival date and time of the route search with “A station” as the arrival station, which is larger than the corresponding period in the past. Can be detected.

  In addition, the information processing apparatus 100 detects an event related to the future by comparing the accumulation of future intention information in which intention is indicated in the first period with the accumulation of past intention information in which intention is indicated in the second period.

  As a result, the information processing apparatus 100 can detect an event related to the future based on the difference between the cumulative transition of future intention information and the cumulative transition of past intention information. Can be detected. For example, when an abnormality occurs, the information processing apparatus 100 accumulates the future intention information at a faster pace than the past intention information accumulation. Can be detected.

  1 shows an example in which the information processing system 1 includes three terminal devices 10A to 10C, one information providing server 50, and one information processing device 100. The system 1 is not limited to three, and may include a plurality of terminal devices 10, a plurality of information providing servers 50, and a plurality of information processing devices 100.

  Further, in FIG. 1, for simplicity of explanation, an example in which the terminal devices 10 </ b> A to 10 </ b> C transmit three intention information is shown, but actually the intention information is transmitted from an unspecified number of terminal devices 10. The information providing server 50 holds a sufficient number of intention information for the abnormality detection by the information processing apparatus 100.

[1-2. Configuration of Information Processing Device According to Embodiment]
Next, the configuration of the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As illustrated in FIG. 3, the information processing apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The information processing apparatus 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator who uses the information processing apparatus 100, and a display unit (for example, a liquid crystal display) that displays various types of information. ).

(About the communication unit 110)
The communication unit 110 is realized by a NIC or the like, for example. The communication unit 110 is connected to a network by wire or wireless, and transmits / receives information to / from the terminal device 10 and the information providing server 50 via the network.

(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 an intention information storage unit 121, a cumulative information storage unit 122, and an abnormality information storage unit 123.

(About the intention information storage unit 121)
The intention information storage unit 121 stores information indicating an intention regarding the user's behavior. Specifically, the intention information storage unit 121 includes past intention information indicating intentions related to past actions from the present time, and future intentions indicating actions corresponding to past actions and indicating future actions for a predetermined period from the present time. Memorize information. For example, the intention information storage unit 121 stores route search information including an arrival date and time and a past arrival place from the present time as past intention information. In addition, the intention information storage unit 121 stores route search information including the arrival date and time and the arrival place in the future for a predetermined period from the current time as future intention information. Here, FIG. 4 shows an example of the intention information storage unit 121 according to the embodiment. As shown in FIG. 4, the intention information storage unit 121 includes items such as “log ID”, “user ID”, “search date / time”, “arrival place”, and “arrival date / time”.

  “Log ID” indicates identification information for identifying intention information. For example, the “log ID” stores a unique identifier that identifies a log of a route search by the user. “User ID” indicates identification information for identifying a user. For example, the “user ID” stores a unique identifier that identifies the user who performed the route search. “Search date and time” indicates the date and time when the user performed a search. For example, “search date and time” stores the date and time when the user performed a route search. The “arrival place” indicates the arrival place designated by the user in the search. For example, in “arrival place”, the name of the arrival station designated by the user in the route search is stored. “Arrival date and time” indicates the arrival date and time specified by the user in the search. For example, “date and time of arrival” stores the date and time of arrival at the station designated by the user in the route search.

  That is, FIG. 4 illustrates an example in which the route search information identified by the log ID “L11” is information searched by the user with the user ID “U11”. Further, the user with the user ID “U11” designates “A station” as the arrival place, designates “17:00” on May 18, 2015 as the arrival date and time, and designates the search date “May 18, 2015 9”. : 01 "shows an example of route search.

  Here, when the current time is “May 25, 2015 10:00”, the route search information identified by the log ID “L11” is the arrival date “May 18, 2015 17:00”. Since it is past from the present time, it is stored as past intention information. Similarly, route search information identified by log IDs “L12 to L13” is stored as past intention information. On the other hand, if the current time is “May 25, 2015 10:00”, the route search information identified by the log ID “L21” is the arrival date “May 25, 2015 17:00” Since it is the future, it is stored as future intention information. Similarly, route search information identified by log IDs “L22 to L24” is stored as future intention information.

(Regarding the cumulative information storage unit 122)
The cumulative information storage unit 122 stores information related to the accumulation of intention information. Specifically, the accumulation information storage unit 122 stores the accumulation of past intention information and the accumulation of future intention information for each place. For example, the cumulative information storage unit 122 stores, for each arrival place, the cumulative number of route searches in which arrival dates and times have been designated in the past from the present time as cumulative past intention information. In addition, the cumulative information storage unit 122 stores, for each arrival place, the cumulative number of route searches in which arrival dates and times are designated in the future for a predetermined period from the present time as the accumulation of future intention information. Here, FIG. 5 illustrates an example of the cumulative information storage unit 122 according to the embodiment. As shown in FIG. 5, the cumulative information storage unit 122 has items such as “location”, “date”, “time”, and “cumulative search number”.

  “Location” indicates a location related to the past or future behavior of the user. For example, the “location” stores the arrival place designated by the route search. “Date” indicates a target date of a period in which the number of route searches is accumulated. “Time” indicates the time of the day that is the target of the period for accumulating the number of route searches. The “accumulated search number” indicates the cumulative number of route searches performed during the period in which the route search number is accumulated. For example, “cumulative search count” stores the cumulative search count of route search in which the target location is designated as the arrival place among the intention information stored in the intention information storage unit 121. As an example, “total number of searches” stores a total value of the number of searches in which route searches have been performed up to the time of the target day of the period for accumulating the number of route searches.

  That is, in FIG. 5, the cumulative number of route searches that specify the place “A station” as an arrival place during the period “May 18, 2015 0:00 to 6:00” is “600”. An example is shown. In addition, during the period “May 18, 2015, 6:00 to 10:00”, the cumulative number of route searches that specify the location “Station A” as the destination is “May 18, 2015, 0:00 Example of "3400" because the cumulative search count for "~ 6: 00" is "600" and the cumulative search count for "May 18, 2015 0:00-10:00" is "4000" Is shown.

  In FIG. 5, the cumulative number of route searches that specify the place “A station” as the arrival point during the period “May 25, 2015, 0:00 to 6:00” is “700”. An example is shown. In addition, during the period of “May 25, 2015, 6:00 to 10:00”, the cumulative number of route searches that specify the location “Station A” as the destination is “May 25, 2015, 0:00 Example of "7300" because the cumulative search count for "~ 6: 00" is "700" and the cumulative search count for "May 25, 2015 0: 00-10: 00" is "8000" Is shown.

(Abnormal information storage unit 123)
The abnormality information storage unit 123 stores information related to events related to the future. Specifically, the abnormality information storage unit 123 stores the location and date and time of an abnormality occurring in the future, the content of the abnormality, the cause of the abnormality, and the like. Here, FIG. 6 illustrates an example of the abnormality information storage unit 123 according to the embodiment. As illustrated in FIG. 6, the abnormality information storage unit 123 includes items such as “event ID”, “event content”, “location”, “date / time”, and “cause”.

  “Event ID” indicates identification information for identifying an event related to the future. For example, the “event ID” stores a unique identifier for identifying an abnormality detected to occur in the future. “Event content” indicates the content of an event related to the future. For example, in “event content”, the content of an abnormality detected to occur in the future is stored. “Place” indicates a place where an event related to the future occurs. For example, “location” stores a location where an abnormality relating to the future occurs. “Date and time” indicates the date and time when an event related to the future occurs. For example, “date and time” stores the date and time of occurrence of an abnormality relating to the future. “Cause” indicates the cause of an event related to the future. For example, “Cause” stores the cause of the occurrence of an abnormality relating to the future.

  That is, FIG. 6 illustrates an example in which the content of the event identified by the event ID “Iv1” is “congested”. Further, an example is shown in which the event identified by the event ID “Iv1” occurs at the place “A station” on the date “May 25, 2015, 17: 00-18: 00”. In addition, an example is shown in which the cause of the event identified by the event ID “Iv1” is “fireworks display”.

(About the control unit 130)
The control unit 130 includes, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like that stores various programs (corresponding to an example of an information processing program) stored in a storage device inside the information processing apparatus 100 in a RAM. This is realized by being executed as a work area. The control unit 130 is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As shown in FIG. 3, the control unit 130 includes an acquisition unit 131, a detection unit 132, a specification unit 133, an adjustment unit 134, a display control unit 135, and a transmission unit 136, which will be described below. Implement or execute information processing functions and actions. 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 past intention information indicating an intention regarding a past action from the present time, and future intention information indicating an action corresponding to the past action and indicating an intention regarding a future action for a predetermined period from the present time. Specifically, the acquisition unit 131 acquires past intention information and future intention information from the information providing server 50 having intention information transmitted from the terminal device 10. For example, the acquisition unit 131 acquires, as past intention information, intention information in which intentions related to past actions are indicated from the present time. As an example, when the current time is “May 25, 2015 10:00”, the acquisition unit 131 designates the place “A station” as the arrival place as past intention information, and specifies the date and time “2015 Route search information that specified “May 18, 17:00” as the arrival date and time is acquired. Further, the acquisition unit 131 acquires, as future intention information, intention information that is an action corresponding to the past action and indicates an intention related to the future action for a predetermined period from the present time. As an example, when the current time is “May 25, 2015, 10:00”, the acquisition unit 131 designates the location “A station” as the arrival location as the future intention information, and the date “2015 Route search information that specifies “25 May 17:00” as the arrival date and time is acquired.

  In addition, when the acquisition unit 131 acquires intention information from the information providing server 50, the acquisition unit 131 stores the acquired intention information in the intention information storage unit 121. For example, the acquisition unit 131 assigns a log ID to the route search information, and associates the user ID, the search date / time, the arrival location, and the arrival date / time included in the route search information with the log ID, and the intention information storage unit 121. To store. The acquisition unit 131 updates the accumulation of intention information stored in the accumulation information storage unit 122 when the intention information is stored in the intention information storage unit 121. For example, when the route information is stored in the intention information storage unit 121, the acquisition unit 131 stores “cumulative” of the route search corresponding to the “arrival place” indicated by the route search information among the data items of the cumulative information storage unit 122. Update “Search Count”.

(About the detector 132)
The detection unit 132 detects an event related to the future based on the past intention information and the future intention information acquired by the acquisition unit 131. Specifically, the detection unit 132 has the future intention information in which the intention is indicated in the first period past from the present time, and the intention corresponding to the first period in the second period that is earlier than the first period. The event related to the future is detected by comparing with the indicated past intention information. For example, the detection unit 132 detects an event related to the future by comparing the accumulation of future intention information in which intention is indicated in the first period and the accumulation of past intention information in which intention is indicated in the second period. As an example, the detection unit 132 detects an event related to the future by comparing the cumulative search number of route searches in the first period in which the same arrival station is specified with the cumulative search number of route searches in the second period.

  In the example of FIG. 5, when the current time is “May 25, 2015 10:00”, the detection unit 132 makes an intention during the first period “May 25, 2015 0:00:00 to 10:00”. Cumulative number of route searches “8000”, which is the accumulation of future intention information indicated by the past, and past intention information whose intention was indicated in the second period “May 18, 2015 0: 00: 00: 00” The future search is detected by comparing the cumulative number of searches for the route search, which is the cumulative total of "4000". In this case, since the accumulation of future intention information is twice as large as the accumulation of past intention information, the detection unit 132 detects an event that congestion occurs at “A station”. In addition, the detection unit 132 detects the future date and time when “A station” is congested based on the arrival date and time of the route search in which “A station” is a larger arrival station than the corresponding period in the past. For example, the detection unit 132 refers to the intention information stored in the intention information storage unit 121, and in the example of FIG. 4, the route search specifying “May 25, 2015, 17: 00-18: 00” as the arrival date and time. Therefore, it detects a future abnormality such as “A station” crowded at “15:00 to 18:00 on May 25, 2015”.

(About the specific part 133)
The identification unit 133 identifies the cause of the event based on the future intention information and the past intention information. Specifically, the specifying unit 133 indicates the future intention information in which the intention is shown in the first period past from the present time and the intention corresponding to the first period and the second period from the first period. The cause of the event is specified based on the content provided by the information providing service within a predetermined period from the time when the difference between the indicated past intention information is equal to or greater than a predetermined threshold. This point will be described with reference to the example of FIG.

  In the example of FIG. 5, the cumulative number of route searches “8000”, which is the accumulation of future intention information indicated during the first period “May 25, 2015 0: 00: 00-10: 00” The difference between the cumulative number of route searches “4000”, which is the accumulation of past intention information indicated during the period “May 18, 2015 0: 00: 00-10: 00”, is “4000 It is. Here, it is assumed that the predetermined threshold is “4000 cases”. In this case, the specifying unit 133 determines that the difference between the future intention information in the first period and the past intention information in the second period is equal to or greater than a predetermined threshold “4000” at “10:00 on May 25, 2015 The cause of the event is specified based on the content provided by the information providing service within a predetermined period. For example, the specifying unit 133 can post a user's post or tweet on the Web on “May 25, 2015, 9: 00-10: 00”, which is within one hour from “May 25, 2015 10:00”. The cause of the event is specified based on an article posted on a shared posting service, news site, SNS (Social Networking Service), or the like. Here, the specifying unit 133 specifies the cause of the event based on the location information indicating the location related to the future action. Specifically, the specifying unit 133 specifies the cause of the event based on the feature word that co-occurs with the location indicated by the location information in the content provided by the information providing service. For example, the location information indicates the arrival location “A station” in the route search as a location related to future actions. Also, it is assumed that the place “A station” and “fireworks display” co-occur in the posted articles provided by the posting service. In this case, the specifying unit 133 specifies “fireworks display” as the cause of the event “crowded” at “A station”.

  Further, the specifying unit 133 stores the cause of the specified event in the abnormality information storage unit 123. For example, the specifying unit 133 assigns an event ID to the event “crowded” at “A station”, and includes the event content “crowded”, the place “A station”, and the date “May 25, 2015, 17: 00-18. : 00 "and the cause" fireworks display "are stored in the abnormality information storage unit 123 in association with the event ID.

(Regarding the adjustment unit 134)
The adjustment unit 134 adjusts a model for calculating a predicted value related to future behavior based on past intention information and future intention information acquired by the acquisition unit 131. Specifically, the adjustment unit 134 adjusts the model by learning the transition of past intention information and the transition of future intention information. For example, the adjustment unit 134 adjusts the model so that the difference between the transition of the predicted value calculated by the model and the transition of the future intention information is small. This point will be described with reference to FIG.

  FIG. 7 is an explanatory diagram for explaining model adjustment. In FIG. 7, the vertical axis of the graph indicates the cumulative number of route searches that designate “A station” as the arrival station. The horizontal axis of the graph indicates time. In the example of FIG. 7, the current time is “May 25, 2015, 10:00”. A graph L11 illustrated in FIG. 7 indicates the cumulative number of route searches in which the user designates “A station” as the arrival station during the period “May 18, 2015, 0:00 to 24:00”. The graph L21 indicates the cumulative number of route searches in which the user designates “A station” as an arrival station during the period “May 25, 2015, 0:00 to 10:00”. In graph L22, the user designates “Station A” as the arrival station during the period “May 25, 2015 10: 00-24: 00”, which is the future from “May 25, 2015 10:00” Indicates the predicted value of the cumulative number of route searches to be performed. The predicted value of the graph L22 is a predicted value calculated by a model that has learned the transition of past intention information on “May 18, 2015, 0:00 to 24:00”. Here, the adjustment unit 134 changes the past intention information of “May 18, 2015 0:00 to 24:00” and the future intention information of “May 25, 2015 0:00 to 10:00”. The model is adjusted by learning the transition of. For example, the adjustment unit 134 adjusts the model so that the difference between the transition of the predicted value calculated by the model and the transition of the future intention information is small. In the example of FIG. 7, the adjustment unit 134 adjusts the model so that the predicted value transition L22 calculated by the model approaches the graph L23 indicating the transition of future intention information. As an example, the adjustment unit 134 adjusts the predicted value calculated by the model to be higher as the accumulated pace of future intention information is faster than the accumulated pace of past intention information. On the other hand, the adjusting unit 134 adjusts the predicted value calculated by the model to be lower as the accumulated pace of future intention information is slower than the accumulated pace of past intention information. For example, the adjustment unit 134 indicates that the predicted value calculated by the model is 0 when the cumulative transition of future intention information is accumulated at a pace 0.93 times that of the cumulative transition of past intention information. Adjust to 93 times.

  Here, the flow of detection processing for detecting an abnormality relating to the future by the information processing system 1, identification processing for specifying the cause of the abnormality, and adjustment processing for adjusting the model will be described with reference to FIG. FIG. 8 is an explanatory diagram for explaining the overall processing flow in the information processing system 1. As illustrated in FIG. 8, the information processing apparatus 100 first acquires intention information from the information providing server 50 (step S11). Subsequently, the information processing apparatus 100 detects an abnormality related to the future based on the acquired past intention information and future intention information (step S12). Thereafter, the information processing apparatus 100 identifies the cause of the abnormality based on the future intention information and the past intention information (step S13). Further, the information processing apparatus 100 adjusts a model for calculating a predicted value related to future behavior based on past intention information and future intention information (step S14). Further, the information processing apparatus 100 stores information regarding the detected abnormality in the abnormality information storage unit 123 (step S15). For example, the information processing apparatus 100 stores information regarding an abnormality in the abnormality information storage unit 123 in association with the identified cause. Note that the information processing apparatus 100 is not limited to the order described above, and may execute the process of step S14 prior to step S12.

(About the display control unit 135)
The display control unit 135 displays information related to the event detected by the detection unit 132 on content provided by an information providing service that accepts past intention information and future intention information. Specifically, the display control unit 135 displays an event on route information (for example, route search result) or schedule information (for example, scheduler) provided by the information providing service. For example, when the user operates the terminal device 10 to search for route information, the display control unit 135 causes the terminal device 10 to display information related to abnormality in the search result of route information. This point will be described with reference to FIG.

  FIG. 9 is a diagram illustrating an example of a screen. When the user searches the route information by operating the terminal device 10, a route information search result screen W <b> 1 is displayed on the terminal device 10 as shown in FIG. 9. Here, on the search result screen W1, congestion information LK such as “congestion is expected” is posted as information on the abnormality. Further, when the user operates the terminal device 10 and selects the congestion information LK on the search result screen W1, as shown in FIG. 9, a detailed screen W2 showing the details of the congestion information LK is displayed on the terminal device 10. Is done. The detail screen W2 includes a place PL “A station” where the abnormality “congestion” detected by the detection unit 132 occurs, a date and time TI “May 25, 2015, 17: 00-18: 00”, and a specifying unit 133 The cause “RE fireworks display” of the abnormality identified by is posted.

  Here, the flow of display processing by the information processing system 1 will be described with reference to FIG. FIG. 10 is an explanatory diagram for explaining the flow of display processing by the information processing system 1. As shown in FIG. 10, first, the terminal device 10 receives an operation from the user and searches for a route of the route (step S21). As a result, the information providing server 50 receives a search result request from the terminal device 10. Thereafter, the information providing server 50 transmits a request for information regarding the abnormality to the information processing apparatus 100 (step S22). For example, the information providing server 50 transmits a request for information regarding an abnormality that occurs on the current day. Subsequently, when the information processing apparatus 100 receives a request for information regarding an abnormality, the information processing apparatus 100 extracts the information regarding the abnormality from the abnormality information storage unit 123 and transmits the information to the information providing server 50 (step S23). For example, the information processing apparatus 100 extracts information related to an abnormality in which the abnormality date and time matches the current date from the abnormality information storage unit 123 and transmits the information to the information providing server 50. Thereafter, when there is an abnormality that occurs in the route searched by the user, the information providing server 50 transmits a search result in which information related to the abnormality is described to the terminal device 10. And the terminal device 10 displays the search result in which the information regarding abnormality was published (step S24). Note that the information providing server 50 transmits a normal search result to the terminal device 10 when there is no abnormality occurring in the route searched by the user. And the terminal device 10 displays a normal search result.

(About transmitter 136)
The transmission unit 136 transmits various types of information to the information providing server 50. Specifically, the transmission unit 136 transmits control information generated by the display control unit 135 to the information providing server 50. For example, when there is a request from the information providing server 50, the transmitting unit 136 transmits control information for displaying information related to the abnormality stored in the abnormality information storage unit 123 to the information providing server 50. As an example, the transmission unit 136 transmits, to the information providing server 50, control information that displays information such as the content of the abnormality, the location where the abnormality occurs, the date and time when the abnormality occurred, the cause of the abnormality, and the like as information regarding the abnormality.

[1-3. Information Processing Procedure According to Embodiment]
Next, a processing procedure performed by the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 11 is a flowchart illustrating an information processing procedure performed by the information processing apparatus 100 according to the embodiment.

  As illustrated in FIG. 11, the information processing apparatus 100 includes past intention information indicating intentions related to past actions from the present time, and a future indicating actions related to the past actions and indicating future actions for a predetermined period from the present time. The intention information is acquired (step S101). Subsequently, the information processing apparatus 100 stores the acquired past intention information and future intention information in the intention information storage unit 121 (step S102).

  Then, the information processing apparatus 100 detects an abnormality relating to the future based on the acquired past intention information and future intention information (step S103). Specifically, the information processing apparatus 100 determines the future intention information in which the intention is shown in the first period past from the present time, and the intention corresponding to the first period in the second period that is past the first period. Compared with past intention information indicated by, an abnormality relating to the future is detected. For example, the information processing apparatus 100 detects an abnormality related to the future by comparing the accumulation of future intention information in which intention is indicated in the first period with the accumulation of past intention information in which intention is indicated in the second period.

  Thereafter, the information processing apparatus 100 identifies the cause of the abnormality based on the future intention information and the past intention information (step S104). Specifically, the information processing apparatus 100 determines the future intention information in which the intention is shown in the first period past from the present time, and the intention corresponding to the first period in the second period that is past the first period. The cause of the abnormality is specified based on the content provided by the information providing service within a predetermined period from the time point when the difference from the past intention information indicated by is greater than or equal to a predetermined threshold. For example, the information processing apparatus 100 identifies the cause of the abnormality based on location information indicating a location related to future actions. As an example, the information processing apparatus 100 identifies the cause of an abnormality based on a feature word that co-occurs with a place indicated by the place information in the content provided by the information providing service. Then, the information processing apparatus 100 stores the cause of the specified abnormality in the abnormality information storage unit 123 (Step S105). For example, the information processing apparatus 100 assigns an event ID to the detected abnormality, and stores the event content, location, date, and cause in the abnormality information storage unit 123 in association with the event ID.

  In addition, the information processing apparatus 100 adjusts a model for calculating a predicted value related to future behavior based on the acquired past intention information and future intention information (step S106). Specifically, the information processing apparatus 100 adjusts the model by learning the transition of past intention information and the transition of future intention information. For example, the information processing apparatus 100 adjusts the model so that the difference between the predicted value transition and the future intention information transition is small.

  Further, the information processing apparatus 100 controls display of information related to abnormality (step S107). Specifically, the information processing apparatus 100 performs display control to display information regarding the detected abnormality on content provided by an information providing service that accepts past intention information and future intention information. For example, the information processing apparatus 100 displays information regarding abnormality in route information or schedule information provided by the information providing service.

[1-4. Effects of the embodiment
As described above, the information processing apparatus 100 according to the embodiment includes the acquisition unit 131 and the detection unit 132. The acquisition unit 131 acquires past intention information indicating an intention regarding a past action from the present time, and future intention information indicating an action corresponding to the past action and indicating an intention regarding a future action for a predetermined period from the present time. The detection unit 132 detects an event related to the future based on the past intention information and the future intention information acquired by the acquisition unit 131. Thereby, since the information processing apparatus 100 detects the event about the future using the past intention information indicating the past action corresponding to the future action, it can detect the abnormality about the future with high accuracy.

  Further, in the information processing apparatus 100 according to the embodiment, the detection unit 132 includes the future intention information in which the intention is indicated in the first period past from the present time, the period corresponding to the first period, and the past from the first period. The event related to the future is detected by comparing with the past intention information in which the intention is shown in the second period. As a result, the information processing apparatus 100 can compare the difference in intention information between the first period in the past from the current time and the second period corresponding to the first period. can do. For example, the information processing apparatus 100 can compare under the same conditions such as the day of the week and the time zone, and can detect an abnormality related to the future with high accuracy. As an example, the information processing apparatus 100 is highly likely that “A station” is congested as an event related to the future when the number of route searches having “A station” as an arrival station is larger than the corresponding period in the past. It can be detected with accuracy. In addition, the information processing apparatus 100 determines the future date and time when “A station” is crowded with high accuracy based on the arrival date and time of the route search with “A station” as the arrival station, which is larger than the corresponding period in the past. Can be detected.

  Further, in the information processing apparatus 100 according to the embodiment, the detection unit 132 compares the accumulation of future intention information in which intention is indicated in the first period with the accumulation of past intention information in which intention is indicated in the second period. To detect future events. As a result, the information processing apparatus 100 can detect an event related to the future based on the difference between the cumulative transition of future intention information and the cumulative transition of past intention information. Can be detected. For example, when an abnormality occurs, the information processing apparatus 100 accumulates the future intention information at a faster pace than the past intention information accumulation. Can be detected.

  The information processing apparatus 100 according to the embodiment may further include a specifying unit 133 that specifies the cause of an event based on future intention information and past intention information. Thereby, since the information processing apparatus 100 specifies the cause of the event based on the user's intention, the cause of the event can be specified with high accuracy.

  Further, in the information processing apparatus 100 according to the embodiment, the specifying unit 133 includes the future intention information in which the intention is indicated in the first period past from the present time, the period corresponding to the first period, and the past from the first period. The cause of the event is specified based on the content provided by the information providing service within a predetermined period from the time point when the difference from the past intention information in which the intention is indicated in the second period exceeds a predetermined threshold. Thereby, the information processing apparatus 100 identifies the cause of the event using real-time information generated within a predetermined period from the time when the difference between the past intention information and the future intention information becomes large. The cause can be identified with high accuracy.

  In the information processing apparatus 100 according to the embodiment, the specifying unit 133 specifies the cause of the event based on the location information indicating the location related to the future action. Thereby, the information processing apparatus 100 can identify the cause from the place related to the event, and therefore can identify the cause of the event with high accuracy.

  In the information processing apparatus 100 according to the embodiment, the specifying unit 133 specifies the cause of the event based on a feature word that co-occurs with the place indicated by the place information in the content provided by the information providing service. Thereby, since the information processing apparatus 100 can specify the cause of the event based on highly credible information, the cause of the event can be specified with high accuracy.

  In addition, the information processing apparatus 100 according to the embodiment further includes a display control unit 135 that displays information on the event detected by the detection unit 132 on content provided by an information providing service that accepts past intention information and future intention information. May be. Thereby, since the information processing apparatus 100 can display the information regarding the event on the user's terminal device 10, the user can be made aware of the event.

  In the information processing apparatus 100 according to the embodiment, the display control unit 135 displays an event on route information or schedule information provided by the information providing service. Thereby, since the information processing apparatus 100 can display the information regarding an event on the terminal device 10 such as a user who searches for route information, for example, the convenience of the user can be improved.

  The information processing apparatus 100 according to the embodiment further includes an adjustment unit 134 that adjusts a model for calculating a predicted value related to future behavior based on past intention information and future intention information acquired by the acquisition unit 131. Also good. Thereby, since the information processing apparatus 100 can make the model learn the future intention information and the past intention information, it can increase the accuracy of the predicted value calculated by the model.

  In the information processing apparatus 100 according to the embodiment, the adjustment unit 134 adjusts the model by learning the transition of past intention information and the transition of future intention information. As a result, the information processing apparatus 100 can cause the model to learn the transition of future intention information and the transition of past intention information up to the present time, so that the accuracy of the predicted value calculated by the model can be improved.

  In the information processing apparatus 100 according to the embodiment, the adjustment unit 134 adjusts the model so that the difference between the predicted value transition and the future intention information transition is small. Thereby, since the information processing apparatus 100 can reduce the error of the predicted value calculated by the model, the accuracy of the predicted value can be increased.

[2. (Modification)
The information processing apparatus 100 according to the above-described embodiment may be implemented in various different forms other than the above-described embodiment. Therefore, hereinafter, another embodiment of the information processing apparatus 100 will be described.

[2-1. Model adjustment)
In the above-described embodiment, an example in which the information processing apparatus 100 adjusts a model that calculates a predicted value related to future behavior based on past intention information and future intention information has been described. Here, the information processing apparatus 100 may adjust the model using various types of information included in past intention information and future intention information as features.

  Specifically, the adjustment unit 134 of the information processing apparatus 100 learns the past intention information and the future intention information using at least one of the information regarding the location, date and time, or environment included in the past intention information and the future intention information as a feature. Adjust the model. For example, the adjustment unit 134 stores various parameters such as “station”, “station type”, “day of the week”, “time”, “weather”, etc. as features, and accumulates past intention information and future intention information with the passage of time. Adjust the model by learning how.

  As described above, the information processing apparatus 100 according to the modified example learns the past intention information and the future intention information using at least one of the information regarding the place, the date and time, or the environment included in the past intention information and the future intention information as a feature. Adjust the model with. Thereby, since the information processing apparatus 100 can learn past intention information and future intention information based on various parameters, the accuracy of the model can be improved.

  Further, the adjustment unit 134 of the information processing apparatus 100 may adjust the model based on an average of transitions of past intention information and future intention information. The adjustment unit 134 may perform noise processing on the accumulated past intention information and future intention information, and may adjust the model by learning the past intention information and future intention information from which noise has been removed. The adjusting unit 134 may adjust the model using a linear classifier. The adjustment unit 134 may adjust the model by adding a device such as matrix decomposition. Thereby, the information processing apparatus 100 can further improve the accuracy of the model.

[2-2. Display control〕
In the above embodiment, the information processing apparatus 100 has been described by taking an example in which information related to an event is displayed on content provided by an information providing service that accepts past intention information and future intention information. Here, the information processing apparatus 100 may perform control so that various types of information are displayed as information related to the event.

  Specifically, the display control unit 135 of the information processing apparatus 100 displays the predicted value calculated from the model adjusted by the adjustment unit 134 on the content provided by the information providing service that accepts past intention information and future intention information. Let For example, the display control unit 135 causes the predicted value calculated from the model adjusted by the adjustment unit 134 to be displayed on route information or schedule information provided by the information providing service. As an example, the display control unit 135 displays the congestion rate of the train based on the predicted value calculated from the model adjusted by the adjustment unit 134 in the search result of the route information.

  As described above, the information processing apparatus 100 according to the modified example displays the predicted value calculated from the model adjusted by the adjustment unit 134 on the content provided by the information providing service that accepts past intention information and future intention information. Thereby, since the information processing apparatus 100 can display the predicted value regarding the future event on the user's terminal device 10, the user can be made aware of the future situation. For this reason, the information processing apparatus 100 can improve user convenience.

  In addition, the information processing apparatus 100 according to the modification displays the predicted value calculated from the model adjusted by the adjustment unit 134 on the route information or the schedule information provided by the information providing service. Thereby, the information processing apparatus 100 can display the congestion rate based on the predicted value in the search result of the route information, the schedule, and the like, so that the user can grasp the future congestion state and the like. For this reason, the information processing apparatus 100 can improve user convenience.

[2-3. (Applicable)
In the above-described embodiment, the information processing apparatus 100 has been described as an example of predicting the congestion situation in the route search as an event related to the future. Here, the information processing apparatus 100 may apply detection of an event related to the future or adjustment of a model to various services, not limited to route search.

  Specifically, the information processing apparatus 100 may be applied to sales prediction of products in a shopping service. In this case, the information processing apparatus 100, for example, as past intention information and future intention information, is settlement information indicating an intention related to past behavior from the present time, and an action corresponding to the past behavior, and a future for a predetermined period from the current time. Using the reservation information indicating the intention regarding the action, it is predicted how much the product will be sold in the future.

  In another example, the information processing apparatus 100 may be applied to stock price prediction in brand search. In this case, the information processing apparatus 100 uses the KW ratio, which is one of the stock price analysis indexes, to predict how much the future stock price will be.

  Thereby, since the information processing apparatus 100 can predict the future situation in various services, the service can be provided efficiently. For example, since the information processing apparatus 100 can predict the sales of a product, various costs can be suppressed by adjusting the number of purchased products and the number of products to appropriate numbers. In another example, since the information processing apparatus 100 can predict a future stock price, the information processing apparatus 100 can provide the user with useful information indicating whether the current time is a buy time or a sell time.

[2-4. Effect of modification)
As described above, in the information processing apparatus 100 according to the modification, the adjustment unit 134 uses the past intention information and the information regarding the location, date and time, or environment included in the past intention information and the future intention information as features. Adjust the model by learning future intention information.

  Thereby, the information processing apparatus 100 according to the modified example can learn past intention information and future intention information based on various parameters, so that the accuracy of the model can be improved.

  Further, in the information processing apparatus 100 according to the modification, the display control unit 135 provides the prediction value calculated from the model adjusted by the adjustment unit 134, provided by the information providing service that accepts past intention information and future intention information. To display.

  Thereby, the information processing apparatus 100 according to the modified example can display a predicted value related to a future event on the user's terminal device 10, so that the user can grasp the future situation. For this reason, the information processing apparatus 100 can improve user convenience.

  In the information processing apparatus 100 according to the modification, the display control unit 135 causes the predicted value calculated from the model adjusted by the adjustment unit 134 to be displayed on route information or schedule information provided by the information providing service.

  Thereby, the information processing apparatus 100 according to the modified example can display the congestion rate based on the predicted value in the search result of the route information, the schedule, and the like, so that the user can grasp the future congestion state and the like. it can. For this reason, the information processing apparatus 100 can improve user convenience.

[3. 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.

  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 intention information storage unit 121 illustrated in FIG. 4 may be stored in a storage server or the like without the information processing apparatus 100. In this case, the information processing apparatus 100 acquires past intention information and future intention information by accessing the storage server.

  Further, the information processing apparatus 100 may be an information processing apparatus that performs only detection processing without performing adjustment processing. In this case, the information processing apparatus does not have the adjustment unit 134. Then, for example, the information processing apparatus having the adjustment unit 134 adjusts the model. Further, the information processing apparatus 100 may be an information processing apparatus that performs only adjustment processing without performing detection processing. In this case, the information processing apparatus does not have the detection unit 132. For example, the information processing apparatus having the detection unit 132 detects an event related to the future. Note that both the detection process and the adjustment process do not necessarily need to be performed, and only one of the processes may be performed.

  Further, the information processing apparatus 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 12, for example. Hereinafter, the information processing apparatus 100 will be described as an example. FIG. 12 is a hardware configuration diagram illustrating an example of a computer 1000 that implements the functions of the information processing 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 programs executed by the CPU 1100, data used by the programs, and the like. The communication interface 1500 receives data from other devices via the communication network N and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the communication network N.

  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. In addition, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

  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. It is.

  For example, when the computer 1000 functions as the information processing 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. However, as another example, these programs may be acquired from other devices via the communication network N.

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

  In addition, the information processing apparatus 100 described above may be realized by a plurality of server computers, and depending on the function, an external platform or the like may be realized by calling an API (Application Programming Interface) or network computing. Can be changed flexibly.

  Further, “section (module, unit)” described in the claims can be read as “means”, “circuit”, and the like. For example, the receiving unit can be read as receiving means or a receiving circuit.

DESCRIPTION OF SYMBOLS 1 Information processing system 10 Terminal device 50 Information providing server 100 Information processing device 121 Intention information storage unit 122 Cumulative information storage unit 123 Abnormal information storage unit 131 Acquisition unit 132 Detection unit 133 Identification unit 134 Adjustment unit 135 Display control unit 136 Transmission unit

Claims (18)

An acquisition unit that acquires past intention information indicating intentions related to past actions from the present time, and future intention information indicating actions corresponding to the past actions and indicating future actions for a predetermined period from the present time;
An information processing apparatus comprising: a detection unit that detects an event related to the future based on past intention information and future intention information acquired by the acquisition unit. The detector is
The future intention information whose intention is shown in the first period past from the present time, and the past intention information which is a period corresponding to the first period and whose intention is indicated in the second period before the first period. And detecting an event related to the future. The detector is
An event relating to the future is detected by comparing the accumulation of future intention information in which the intention is indicated in the first period with the accumulation of past intention information in which the intention is indicated in the second period. Item 3. The information processing device according to Item 2. The information processing apparatus according to claim 1, further comprising: a specifying unit that specifies a cause of the event based on the future intention information and the past intention information. The specific part is:
Future intention information whose intention was shown in the first period past from the present time, and past intention information which is a period corresponding to the first period and whose intention was shown in the second period before the first period 5. The information processing apparatus according to claim 4, wherein the cause of the event is specified based on content provided by the information providing service within a predetermined period from a time point when the difference between the two becomes a predetermined threshold value or more. . The specific part is:
The information processing apparatus according to claim 4, wherein the cause of the event is specified based on location information indicating a location related to the future action. The specific part is:
The information processing apparatus according to claim 6, wherein the cause of the event is specified based on a feature word that co-occurs with a location indicated by the location information in the content provided by the information providing service. The display control part which displays the information regarding the event detected by the said detection part on the content which the information provision service which receives the said past intention information and the said future intention information is further provided. The information processing apparatus according to any one of the above. The display control unit
The information processing apparatus according to claim 8, wherein the event is displayed on route information or schedule information provided by the information providing service. The adjustment part which adjusts the model which calculates the predicted value regarding the said future action based on the past intention information and future intention information which were acquired by the said acquisition part, The further characterized by the above-mentioned. The information processing apparatus according to one. The adjustment unit is
The information processing apparatus according to claim 10, wherein the model is adjusted by learning transition of the past intention information and transition of the future intention information. The adjustment unit is
The information processing apparatus according to claim 11, wherein the model is adjusted so that a difference between the transition of the predicted value and the transition of the future intention information is small. The adjustment unit is
The model is adjusted by learning the past intention information and the future intention information using at least one of the information regarding the place, date and environment included in the past intention information and the future intention information as a feature. The information processing apparatus according to any one of claims 10 to 12. The display control unit for displaying a predicted value calculated from the model adjusted by the adjustment unit on content provided by an information providing service that accepts the past intention information and the future intention information. The information processing apparatus according to any one of 10 to 13. The display control unit
The information processing apparatus according to claim 14, wherein a predicted value calculated from the model adjusted by the adjustment unit is displayed on route information or schedule information provided by the information providing service. An acquisition unit that acquires past intention information indicating intentions related to past actions from the present time, and future intention information indicating actions corresponding to the past actions and indicating future actions for a predetermined period from the present time;
An information processing apparatus comprising: an adjustment unit that adjusts a model that calculates a predicted value related to the future action based on past intention information and future intention information acquired by the acquisition unit. An information processing method executed by an information processing apparatus,
An acquisition step of acquiring past intention information indicating an intention regarding a past action from the present time, and future intention information indicating an action corresponding to the past action and indicating a future action for a predetermined period from the present time;
A detection step of detecting an event related to the future based on past intention information and future intention information acquired by the acquisition step. An acquisition procedure for acquiring past intention information indicating an intention regarding a past action from the present time, and future intention information indicating an action corresponding to the past action and indicating a future action for a predetermined period from the present time;
An information processing program causing a computer to execute a detection procedure for detecting an event relating to the future based on past intention information and future intention information acquired by the acquisition procedure.

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