JP2020013502A - Device, method, and program for processing information - Google Patents

Abstract

To provide a device, method, and program for processing information, which allow for browsing video content even in less than optimal communication environments.SOLUTION: An information processing device of the present invention includes a prediction unit and a determination unit. The prediction unit predicts browsing hours when a user browses content. The determination unit determines acquisition data to be acquired in advance by a user terminal on the basis of the browsing hours predicted by the prediction unit.SELECTED DRAWING: Figure 1

Description

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

  2. Description of the Related Art In recent years, with the dramatic spread of the Internet and the improvement of distribution technology, it has become possible to browse various contents via the Internet. For example, many people view video contents such as movies and dramas via the Internet.

JP 2013-142935 A

  However, since the moving image content has a larger amount of information than the content of a still image such as text, in an environment without a Wi-Fi communication environment, browsing of the moving image content becomes unstable or a huge communication cost is required. For example, it may be difficult to browse video content.

  The present application has been made in view of the above, and provides an information processing apparatus, an information processing method, and an information processing program capable of realizing browsing of moving image content even in an environment where an optimal communication environment is not prepared. With the goal.

  An information processing device according to the present application includes a prediction unit and a determination unit. The prediction unit predicts a browsing time period during which the user browses the content. The deciding unit decides the acquisition data to be acquired in advance by the user terminal based on the browsing time zone predicted by the prediction unit.

  According to an aspect of the embodiment, it is possible to provide an information processing apparatus, an information processing method, and an information processing program capable of realizing browsing of moving image content even in an environment where an optimal communication environment is not prepared.

FIG. 1 is an explanatory diagram illustrating an example of an information processing method according to the embodiment. FIG. 2 is an explanatory diagram illustrating an example of a configuration of the information processing system according to the embodiment. FIG. 3 is an explanatory diagram illustrating an example of a configuration of the information processing apparatus according to the embodiment. FIG. 4 is an explanatory diagram illustrating an example of a learning model storage unit according to the embodiment. FIG. 5 is an explanatory diagram illustrating an example of an operation of the information processing device according to the embodiment. FIG. 6 is an explanatory diagram illustrating an example of an operation of the information processing device according to the embodiment. FIG. 7 is an explanatory diagram illustrating an example of an operation of the information processing device according to the embodiment. FIG. 8 is an explanatory diagram illustrating an example of an operation of the information processing device according to the embodiment. FIG. 9 is a flowchart illustrating a process executed by the control unit of the information processing apparatus according to the embodiment. FIG. 10 is a hardware configuration diagram illustrating an example of a computer that implements the functions of the information processing apparatus according to the embodiment.

  Hereinafter, an information processing apparatus, an information processing method, and a mode for executing 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, the information processing method, and the information processing program according to the present application are not limited by the embodiment. In addition, the embodiments can be appropriately combined within a range that does not contradict processing contents. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description will be omitted.

[1. Information processing method)
First, an information processing method performed by the information processing apparatus 1 according to the embodiment will be described. FIG. 1 is an explanatory diagram illustrating an example of an information processing method according to the embodiment. Here, a description will be given of an information processing method performed when the user terminal 2 acquires and reproduces the content V1 which is moving image content from the content distribution device 3 (see FIG. 2) via the wireless communication network N.

  Note that the content V1 is not limited to the moving image content illustrated in FIG. 1 and may be a content that does not include a moving image (for example, a news site).

  Here, the black triangles shown in (a) to (c) of FIG. 1 are acquisition pointers D indicating the part of the entire content V1 that the user terminal 2 is acquiring. The white triangles shown in (a) to (c) of FIG. 1 are reproduction pointers P indicating the part of the entire content V1 being reproduced by the user terminal 2. Note that the hatched portions shown in (a) to (c) of FIG. 1 indicate portions where the user terminal 2 is buffering in the entire content V1.

  As shown in FIG. 1A, the user terminal 2 can acquire and reproduce the content V1 from a content distribution device 3 that distributes the content V1 via a network N, such as a smartphone or a tablet terminal. It is a portable mobile terminal device. The user terminal 2 simultaneously reproduces the content V1 while sequentially acquiring the content V1.

  For this reason, in the examples shown in FIGS. 1A to 1C, when the user terminal 2 acquires and reproduces the content V1, the acquisition pointer D and the reproduction pointer P move from the left with the passage of time. Move right.

  The communication environment of the user terminal 2 is not always the same. More specifically, since the user terminal 2 is a portable terminal device, the user terminal 2 changes from a Wi-Fi communication environment that is an optimal communication environment for reproducing a moving image to another communication environment that is not optimal for reproducing a moving image (for example, 3G ( Generation) or 4G), and vice versa.

  Therefore, the information processing apparatus 1 according to the embodiment models the behavior of the user in advance, and determines the acquisition data Va of the browse content V acquired in advance from the content distribution apparatus 3 based on the modeled behavior of the user. . Then, the user terminal 2 pre-acquires the acquired data Va of the determined browse content V from the content distribution device 3.

  For example, as illustrated in FIG. 1A, the information processing device 1 creates an action model M that models a user's action history. The behavior model M includes, for example, user's behavior histories such as position information and Wi-Fi observation information of the user terminal 2, operation histories that are histories of operations on the user terminal 2, and browsing histories that are histories of content browsing. Can be created based on

  For example, in the example shown in FIG. 1A, the behavior model M includes the user who is at home from time T1 to time T2 when browsing of the content V1 is started, travels from time T2 to time T3 by commuting, After time T3, it is modeled to be in the company. Although not shown in FIG. 1, the behavior model M has a browsing history of the moving image content in a commuting time zone from time T2 to time T3.

  Therefore, the information processing apparatus 1 predicts the time zone from the moving time T2 to the time T3 at the time T1 at which the browsing of the moving image content is started as a “browsing time zone” (step S01). The browsing time period is, for example, because the user terminal 2 is not in a Wi-Fi communication environment and is not in an environment that is optimal for moving image reproduction. Is the time zone in which the browsing history exists. That is, the viewing time period is a time period in which the user is highly likely to view the moving image content based on the viewing history of the moving image content.

  Next, at the time T1, the information processing device 1 predicts a content to be browsed in the predicted browsing time zone (hereinafter, also referred to as browsed content V). For example, as shown in FIG. 1A, when the content V1 being viewed at time T1 is a volume that can be viewed from time T2 to time T3, the user views the continuation of the content V1 in the viewing time zone. Likely to be. Therefore, in this case, the information processing device 1 predicts the content V1 as the browse content V (step S02).

  Next, at time T1, the information processing apparatus 1 acquires the acquired data Va that the user terminal 2 acquires in advance based on the predicted browse content V and the browse time zone, as shown in FIG. Is determined (step S03). For example, the information processing device 1 determines, as the acquired data Va, a portion of the browse content V corresponding to the browse time zone (that is, from time T2 to time T3). Then, the information processing device 1 instructs the user terminal 2 to acquire the determined acquisition data Va from the time T1.

  That is, from time T1 to time T2, the browsing content V, which is a moving image content, has already been viewed at home, and it is predicted that, from time T2, the continuation of the browsing content V is reproduced as a moving image. The user terminal 2 is instructed to acquire moving image data from time T2 to time T3 in consideration of the travel time from time T1.

  Then, as shown in FIG. 1C, the user terminal 2 performs the pre-acquisition of the determined acquisition data Va while reproducing the content V1 from the time T1 at which the browsing of the moving image content is started. Do it. Note that a black triangle adjacent to the acquired data Va in FIG. 1C is a pre-obtained pointer Da indicating a part of the entire browsed content V that is being pre-acquired by the user terminal 2.

  Then, when the acquisition of the acquisition data Va is completed, the user terminal 2 ends the advance acquisition of the acquisition data Va indicated by the advance acquisition pointer Da. Note that the user terminal 2 continues to acquire the content V1 being viewed and indicated by the acquisition pointer D while acquiring the acquired data Va.

  Thereby, even if the user terminal 2 is placed in an environment other than the Wi-Fi communication environment from time T2 to time T3, the user terminal 2 has already acquired the acquisition data Va at that time. It is possible to browse a certain browse content V comfortably. That is, according to the embodiment, it is possible to realize browsing of the moving image content even when the environment is not optimal for reproducing the moving image.

  Further, in the embodiment, when the user moves from the fixed-rate Wi-Fi communication environment to the 3G or 4G communication environment with the pay-as-you-go system, the obtained data Va has already been obtained, so that the browsing contents V can be viewed while suppressing the communication cost. can do.

  In addition, the information processing apparatus 1 determines a portion corresponding to the browsing time zone in the browsing content V as the acquisition data Va. Thereby, the data amount of the acquired data Va acquired in advance can be suppressed, so that the limited storage area of the user terminal 2 can be utilized without waste.

  In addition, the information processing device 1 predicts a browsing time zone based on an action model M that models the action history of the user. Thereby, it is possible to predict the browsing time zone based on the usual action taken by the user.

[2. Configuration of information processing system]
Next, a configuration of the information processing system 100 according to the embodiment will be described with reference to FIG. FIG. 2 is an explanatory diagram illustrating an example of a configuration of the information processing system 100 according to the embodiment. As illustrated in FIG. 2, the information processing system 100 according to the embodiment includes an information processing device 1, a user terminal 2, and a content distribution device 3.

  The information processing device 1 is, for example, a server and creates an action model M that models the action history of the user. In addition, for example, when there is a request for browsing the content V1 from the user terminal 2 to the content distribution device 3, the information processing device 1 predicts the browsing time zone and the browsing content V, and determines the acquisition data Va of the browsing content V. .

  The user terminal 2 is a portable wireless terminal such as a smartphone, a tablet terminal, and a mobile PC (Personal Computer). The content distribution device 3 is, for example, a PC. Distribute V1.

  The information processing apparatus 1, the user terminal 2, and the content distribution apparatus 3 establish a network (for example, the Internet) N by wireless LAN (Local Area Network) communication, WAN (Wide Area Network) communication, mobile phone communication, or the like. And various types of information can be communicated between them.

[3. Configuration of information processing device]
Next, a configuration of the information processing apparatus 1 according to the embodiment will be described with reference to FIG. FIG. 3 is an explanatory diagram illustrating an example of a configuration of the information processing apparatus 1 according to the embodiment. As shown in FIG. 3, the information processing device 1 includes a communication unit 11, a storage unit 12, and a control unit 13. The information processing apparatus 1 includes an input unit (for example, a keyboard and a mouse) for receiving various operations from an administrator or the like using the information processing apparatus 1, and a display unit (for example, a liquid crystal display) for displaying various information. Etc.).

(About the communication unit 11)
The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 11 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the user terminal 2 and the content distribution device 3 via the network N.

(About the storage unit 12)
The storage unit 12 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 3, the storage unit 12 includes a learning data storage unit 121 and a model 122.

(About the learning data storage unit 121)
The learning data storage unit 121 stores the user's action history acquired from the user terminal 2. FIG. 4 is an explanatory diagram illustrating an example of the learning data storage unit 121 according to the embodiment.

  The learning data storage unit 121 illustrated in FIG. 4 has items such as “time zone”, “action”, “browsing history of moving image content”, and “Wi-Fi communication environment”. Further, as shown in FIG. 4, the learning data storage unit 121 has different learning data storage units 121a, 121b, 121c,... For each user.

  “Time zone” indicates each time zone for each action of the user. “Action” indicates the action of the user for each time slot. The “action” is estimated from the position history of the user terminal 2. The “moving content browsing history” indicates whether there is a history of browsing of the moving image content by the user for each time slot. The “Wi-Fi communication environment” indicates whether there is a Wi-Fi communication environment around the user.

  That is, in the example of FIG. 4, the “action” of the user A whose “time zone” is from time T0 to time T2 (hereinafter also referred to as “T0 to T2”) is “at home”. The “moving content browsing history” is “present”, and the “Wi-Fi communication environment” is “present”.

  The “action” of the user A whose “time zone” is from time T2 to time T3 (hereinafter also referred to as “T2 to T3”) is “commuting”. "Is" present ", indicating that" Wi-Fi communication environment "is" none ".

  Further, the “action” of the user A whose “time zone” is from the time T3 to the time T4 (hereinafter also referred to as “T3 to T4”) is “work at a company”. This indicates that the “viewing history” is “none” and the “Wi-Fi communication environment” is “present”.

  Although not shown in FIG. 4, the data of the “time zone” includes information of the day of the week in addition to the time. Thus, in the embodiment, since it is possible to distinguish between a weekday and a holiday, for example, since commuting is not performed on a holiday, it is possible to prevent acquisition of data corresponding to the time of traveling by commuting on a weekday.

  In addition, the learning data storage unit 121 in which the user's action history is collected in this way is the user's position information acquired from the user terminal 2 or the like, Wi-Fi communication observation information, and operation history for the user terminal 2. It can be created based on an operation history, a browsing history that is a history of browsing contents, and the like.

  The learning data storage unit 121 can be created by applying various known methods, for example, maximum likelihood estimation, averaging processing, matrix factorization, and the like.

(About the model 122)
The model 122 stores an action model M that models the action history of the user. For example, the model 122 is realized by an arbitrary classifier such as an SVM (Support Vector Machine) and a DNN (Deep Neural Network). Here, the DNN may be a CNN (Convolutional Neural Network) or an RNN (Recurrent Neural Network). Further, the RNN may be LSTM (Long Short-Term Memory) or the like.

(About the control unit 13)
The control unit 13 is a controller, for example, various programs stored in a storage device inside the information processing apparatus 1 (for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit)). (Corresponding to an example) is executed by using the RAM as a work area. The control unit 13 is, for example, a controller, and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

  As illustrated in FIG. 3, the control unit 13 includes a reception unit 131, a model creation unit 132, a prediction unit 133, a determination unit 134, and an instruction unit 135, and functions and functions of information processing described below. Realize or execute. Note that the internal configuration of the control unit 13 is not limited to the configuration illustrated in FIG. 3 and may be another configuration as long as the configuration performs information processing described below.

(About the reception unit 131)
The receiving unit 131 receives various information. For example, the receiving unit 131 receives various information related to the user's action history, such as the position information of the user terminal 2 and the observation information of the Wi-Fi communication. In addition, when the user terminal 2 requests the content distribution device 3 to view the content V1, the receiving unit 131 receives, from the user terminal 2 or the like, the request to view the content V1.

(About the model creation unit 132)
The model creation unit 132 creates a learning data storage unit 121 that summarizes the user's action history and a model 122 that models the user's action history. For example, the model creating unit 132 creates the learning data storage unit 121 based on various types of information on the user's action history received by the receiving unit 131.

  For example, when the user terminal 2 receives an action history in which the user terminal 2 moves from the home position to the company position in the time period T2 to T3, the model creating unit 132 estimates that the user A has moved from the home to the company. . Accordingly, the model creation unit 132 can cause the learning data storage unit 121 to store that the behavior of the user A in the time period T2 to T3 is commuting.

  In addition, when the model creation unit 132 receives the action history of viewing the moving image content in the time period T2 to T3, the model creation unit 132 stores the browsing history of the moving image content in the time period T2 to T3 as “Yes” in the learning data storage unit 121. Can be done.

  Further, the model creating unit 132 creates the model 122 based on the learning data storage unit 121. Specifically, the model creation unit 132 outputs a backproperty so as to output information indicating a browsing history of video content when information indicating a time zone, an action, and a Wi-Fi communication environment of learning data is input. The technique of the action history is made to be learned by the model 122 by using a technique such as gating.

  More specifically, the model creation unit 132 listens to the model 122 by listening to the moving image content at what time zone, in what kind of communication environment, and what kind of action the user is performing. Is made to learn by the model 122.

  In addition, the model creation unit 132 causes the model 122 to learn arbitrary information such as the user's attributes and weather, as well as the time zone, the behavior, and the communication environment, and the relationship whether the user has previewed the moving image. You may.

  Further, the model creating unit 132 may use only a part of the information described above. That is, the model creating unit 132 may learn an arbitrary model as long as the model estimates whether or not the user views the moving image content in a predetermined time zone.

(About the prediction unit 133)
The prediction unit 133 predicts the browse content V (see FIG. 1) browsed by the user and the browse time zone in which the browse content V is browsed. For example, the prediction unit 133 predicts a browsing time zone by using information stored in the model 122 and various information related to the user's action history received by the reception unit 131.

  For example, the prediction unit 133 uses the model 122 to browse “time zones T2 to T3” in which “Wi-Fi communication environment” is “none” and “video content browsing history” is “present”. Predict as a band. This is because “time zone T2 to T3” does not have a Wi-Fi communication environment, that is, it is not an environment optimal for moving image reproduction, but has a need for buffering since there is a history of browsing of moving image contents in the past. This is because it is considered a time zone.

  Further, the prediction unit 133 predicts the browse content V based on, for example, content information (for example, the content V1) for which a browse request has been issued from the user terminal 2. For example, the prediction unit 133 predicts the content V1 as the browsed content V when the volume of the content V1 is browsable in a time period T2 to T3 which is a browse time period.

  Further, the prediction unit 133 acquires attribute information indicating the attribute of the user, and can predict as the browse content V based on the attribute information of the user by applying various known methods.

  For example, the prediction unit 133 can predict content corresponding to the attribute information of the user as the browse content V. For example, when the attribute information of the user indicates a woman, the prediction section 133 can select, as the viewed content V, a content whose browsing history by a woman is large.

  In the embodiment, the attribute information of the user may be a demographic attribute or a psychographic attribute. The attribute information of the user may be registered in advance, or may be information estimated by various known estimation techniques.

(About the decision unit 134)
The determination unit 134 determines the acquisition data Va that the user terminal 2 acquires in advance based on the browse content V and the browse time zone predicted by the prediction unit 133. The determining unit 134 determines, for example, a portion of the browsed content V that is reproduced in a time period T2 to T3, which is a browse time period, as the acquisition data Va.

(About the instruction unit 135)
The instruction unit 135 instructs the user terminal 2 to pre-acquire the acquired data Va when receiving the data related to the acquired data Va from the determination unit 134. For example, the instruction unit 135 instructs the user terminal 2 to pre-acquire the acquisition data Va from the time T1 at which the browsing of the moving image content is started. This allows sufficient time for buffering the moving image content, so that the moving image content can be browsed without any problem even in an environment where an optimal communication environment is not prepared.

  The timing at which the instruction unit 135 causes the user terminal 2 to start pre-acquisition of the acquired data Va is not limited to the time T1 when the browsing of the moving image content is started, and is not limited to the time T2 when commuting is started from the time T1. Any timing may be used as long as it is before the time point.

[4. Operation of information processing device]
Next, an example of the operation of the information processing apparatus 1 will be described with reference to FIGS. 5 to 8 are explanatory diagrams illustrating an example of the operation of the information processing device 1.

[4-1. Predict another content)
As shown in FIG. 5A, when there is a request for browsing the content V1 that is a moving image content from the user terminal 2 to the content distribution device 3 at time T1, the information processing device 1 performs the browsing request for the content V1. Is received from the user terminal 2 or the like. Then, at the time T1 at which the browsing of the moving image content is started, the information processing device 1 predicts the time period T2 to T3 as the browsing time period based on the user's behavior model M stored in the model 122 ( Step S11).

  Here, in the example shown in FIG. 5, unlike the example of FIG. 1, the content V1 is not a volume that can be browsed from time T2 to time T3, and the browse ends at time T1a before time T2.

  In this case, at the time T1, the information processing apparatus 1 predicts a content different from the content V1 as the browse content V as shown in FIG. 5B (step S12). For example, the information processing apparatus 1 can predict content related to the content V1 requested to be browsed at time T1 (for example, the next story or sequel to the content V1) as the browsed content V.

  Thereby, the information processing apparatus 1 can cause the user terminal 2 to acquire in advance the content that is likely to be browsed in the subsequent browse time zone as the browse content V from the time T1.

  Further, the information processing device 1 can predict the browse content V based on the attribute information of the user. Accordingly, the information processing apparatus 1 can predict the browsed content V even when the content is not browsed on the user terminal 2 at the time of prediction.

  Next, as shown in FIG. 5B, the information processing apparatus 1 acquires the acquired data Va that the user terminal 2 acquires in advance based on the predicted browse content V and the browse time zone at the time T1. Is determined (step S13). Then, the information processing device 1 instructs the user terminal 2 to acquire the determined acquisition data Va from the time T1.

  Then, as shown in FIG. 5C, the user terminal 2 performs the pre-acquisition of the determined acquisition data Va from the time T1 at which the browsing of the moving image content is started. Then, as shown in FIG. 5D, when the acquisition of the acquisition data Va is completed, the user terminal 2 ends the advance acquisition of the acquisition data Va indicated by the advance acquisition pointer Da.

  Thereby, the information processing device 1 can cause the user terminal 2 to acquire the browsed content V in advance even when the content V1 being browsed at the time of prediction is not a volume that can be browsed until the browse time zone.

[4-2. News site pre-acquisition)
In the example described so far, the case where the browsed content V is a moving image content is shown, but the browsed content V is not limited to the moving image content. FIG. 6 illustrates a case where the browsed content V is a news site as another example of the browsed content V.

  As shown in FIG. 6A, when there is a browsing request for the news site NS from the user terminal 2 to the content distribution device 3 at time T1, the information processing device 1 receives the browsing request for the news site NS. Is received from the user terminal 2 or the like. Then, the information processing device 1 predicts the time zone T2 to T3 as the viewing time zone based on the user behavior model M stored in the model 122 (step S21).

  Then, when the news site NS being browsed at time T1 has a volume that can be browsed from time T2 to time T3, the information site 1 predicts the news site NS as the browsed content V (step S22).

  Next, as shown in FIG. 6B, the information processing device 1 determines the acquisition data Va that the user terminal 2 acquires in advance based on the predicted browse content V and the browse time zone (step S23). ).

  In the example shown in FIG. 6B, when the "main" column of the news site NS is browsed at the time T1, the information processing apparatus 1 sets the news site NS in the browse time zone (time zone T2 to T3). It is predicted that the “sports” column and “IT” column will be browsed, and the “sports” column and “IT” column are determined as the acquired data Va. Then, the information processing device 1 instructs the user terminal 2 to acquire the determined acquisition data Va.

  Thereby, the information processing apparatus 1 can cause the user terminal 2 to acquire the browse content V in advance even when the browse content V is not a moving image content. In addition, the example of the browse content V is not limited to the video content or the news site, and may be any content as long as the content can be acquired and browsed in advance by the user terminal 2.

  For example, the browse content V is related to a portal site, a news site, an auction site, a weather forecast site, a shopping site, a finance (stock price) site, a route search site, a map providing site, a travel site, a restaurant introduction site, a web blog, and the like. Various contents.

[4-3. Prediction of browsing time zone based on schedule)
In the example described so far, the case where the browsing time zone is predicted based on the behavior model M obtained by modeling the behavior history of the user has been described, but the information means for predicting the browsing time zone is not limited to the behavior model M. 7 and 8, a method of predicting a browsing time zone based on information means other than the behavior model M will be described.

  As illustrated in FIG. 7, when a user's schedule is registered in the user terminal 2 or the like, the information processing device 1 can predict a viewing time zone based on the user's schedule.

  First, the information processing device 1 acquires schedule information of a user from the user terminal 2 or the like (step S31). For example, as shown in FIG. 7, when “13:00 to 14:00 move to the head office by train” is registered in the user's schedule, the information processing apparatus 1 receives the keyword “move by train” from the keyword. At the time of the schedule, it is predicted that the environment is not optimal for reproducing the moving image.

  Therefore, the information processing apparatus 1 predicts the time zone “13:00 to 14:00” of the schedule as the viewing time zone (step S32). Thereafter, the information processing device 1 predicts the browse content V as described above, and determines the acquisition data Va based on the predicted browse time zone and the browse content V.

  Thereby, the information processing apparatus 1 can predict the browsing time zone even when the user's behavior is different from the usual behavior.

[4-4. Prediction of browsing time zone based on transfer guidance)
In addition, as shown in FIG. 8, when the user uses the transfer guide service of various transportation means at the user terminal 2 or the like, the information processing apparatus 1 predicts the browsing time zone based on the search result of the transfer guide service. can do.

  First, the information processing apparatus 1 acquires information on a search result of the transfer guidance service from the user terminal 2 or the like (step S41). If the search result is "12:00 Shinagawa departure-Yamanote line-12: 20 Shinjuku arrival", the information processing apparatus 1 is not in an environment optimal for moving image reproduction during the moving time. Predict.

  Therefore, the information processing device 1 predicts the time zone “12: 00-12: 20” of the travel time as the viewing time zone (step S42). Thereafter, the information processing device 1 predicts the browse content V as described above, and determines the acquisition data Va based on the predicted browse time zone and the browse content V.

  Thereby, the information processing device 1 can predict the browsing time zone based on a specific action that the user is likely to take.

[4-5. Prediction of viewing time zone based on other information)
The other information means for estimating the browsing time zone is not limited to the schedule information and the search result of the transfer guidance service, but may be any information that occurs before the user acts and can be acquired by the information processing apparatus 1. Any information may be used.

  For example, the information processing device 1 estimates a user's travel time zone based on timetable data stored in advance in the storage unit 12 and the acquired user's action schedule, and sets the travel time zone as a browse time zone. It may be predicted. In addition, the information processing device 1 may predict a browsing time zone based on a schedule registered in a user's calendar. Furthermore, the information processing device 1 may predict the viewing time zone based on the contents of the e-mail sent and received by the user.

  Based on such various information, a case where the normal behavior pattern is different from the normal behavior pattern by estimating a user's behavior pattern different from the normal behavior pattern and estimating a browsing time zone according to the estimated behavior pattern. However, buffering of moving image contents and the like can be realized.

[4-6. Acquisition of edited browsing content)
Further, in the embodiment, the example has been described in which the portion corresponding to the browsing time zone is acquired as it is as the acquisition data Va in the browsing content V that is the moving image content, but the edited browsing content V is acquired as the acquisition data. Is also good.

  For example, when the browsed content V is a news video of 1 hour in length, and the length of the browse time zone is predicted to be 45 minutes, the information processing apparatus 1 converts the news video of 1 hour in length to 45 minutes. Edit to length. Then, the user terminal 2 may acquire the news moving image edited to have a length of 45 minutes as the acquisition data Va.

[5. Processing procedure)
Next, a process executed by the control unit 13 of the information processing device 1 will be described with reference to FIG. FIG. 9 is a flowchart illustrating a process executed by the control unit 13 of the information processing device 1 according to the embodiment.

  As shown in FIG. 9, the control unit 13 first predicts a browsing time zone (step S101). For example, the control unit 13 predicts a viewing time zone based on the user's behavior model M stored in the model 122 of the storage unit 12.

  Next, the control unit 13 determines whether there is any content being browsed on the user terminal 2 (Step S102). Then, when there is content being browsed on the user terminal 2 (step S102, Yes), the control unit 13 determines whether or not the content being browsed has a volume that can be browsed until the browse time zone (step S103). ).

  If the currently viewed content has a volume that can be viewed until the viewing time zone (step S103, Yes), the control unit 13 predicts the currently viewed content as the viewed content V (step S104).

  Next, the control unit 13 determines the acquired data Va based on the predicted viewing time zone and the viewing content V (step S105). Then, the control unit 13 instructs the user terminal 2 to acquire the acquired data Va in advance (Step S106), and ends the processing.

  On the other hand, in Step S102, when there is no content being browsed on the user terminal 2 (Step S102, No), the control unit 13 predicts the browse content V based on the attribute information indicating the attribute of the user (Step S107), The process moves to step S105.

  Further, in step S103, when the content being viewed does not have a volume that can be viewed until the viewing time zone (No in step S103), the control unit 13 shifts the processing to step S107.

[6. Hardware configuration)
The information processing apparatus 1 according to the embodiment is realized by, for example, a computer 50 having a configuration as illustrated in FIG. FIG. 10 is a hardware configuration diagram illustrating an example of a computer that implements the functions of the information processing device 1. The computer 50 includes a CPU (Central Processing Unit) 51, a RAM (Random Access Memory) 52, a ROM (Read Only Memory) 53, a HDD (Hard Disk Drive) 54, a communication interface (I / F) 55, and an input / output interface (I / F) 56 and a media interface (I / F) 57.

  The CPU 51 operates based on a program stored in the ROM 53 or the HDD 54 and controls each unit. The ROM 53 stores a boot program executed by the CPU 51 when the computer 50 is started, a program depending on hardware of the computer 50, and the like.

  The HDD 54 stores a program executed by the CPU 51, data used by the program, and the like. The communication interface 55 corresponds to the communication unit 11, receives data from another device via the network N, sends the data to the CPU 51, and transmits the data generated by the CPU 51 to the other device via the network N.

  The CPU 51 controls output devices such as a display and a printer and input devices such as a keyboard and a mouse via an input / output interface 56. The CPU 51 acquires data from an input device via the input / output interface 56. Further, the CPU 51 outputs the generated data to the output device via the input / output interface 56.

  The media interface 57 reads a program or data stored in the recording medium 58 and provides the program or data to the CPU 51 via the RAM 52. The CPU 51 loads the program from the recording medium 58 onto the RAM 52 via the media interface 57, and executes the loaded program. The recording medium 58 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc), a 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. And so on.

  For example, when the computer 50 functions as the information processing apparatus 1 according to the embodiment, the CPU 51 of the computer 50 implements the function of the control unit 13 by executing a program loaded on the RAM 52. The HDD 54 stores data in the storage unit 12. The CPU 51 of the computer 50 reads these programs from the recording medium 58 and executes them. However, as another example, these programs may be obtained from another device via the network N.

[7. Others)
Further, of the processes described in the above embodiment, all or a part of the processes described as being performed automatically can be manually performed, or the processes described as being performed manually can be performed. All or part can be performed automatically by a known method. In addition, the processing procedures, specific names, and information including 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 information shown.

  Each component of each device illustrated is a functional concept, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part thereof may be functionally or physically distributed / arbitrarily divided into arbitrary units according to various loads and usage conditions. Can be integrated and configured. For example, in the embodiment, the example in which the terminal that browses the content V1 at home and the terminal that browses the browsed content V during the browse time zone are performed by the same user terminal 2 is described. The terminal that browses the browse content V during the browse time zone is not limited to the same terminal.

  For example, when the user browses the content V1 on an installation terminal installed at home, the information processing apparatus 1 may instruct a smartphone having the same user ID as the installation terminal to acquire the browse content V in advance. .

  In the embodiment, the browsing time zone is predicted using the model 122 created by the model creating unit 132. However, the embodiment is not limited to this. For example, the browsing time zone may be predicted on a rule basis. For example, since a moving image can be seen during commuting between 9:00 and 10:00 on weekdays, such a time zone may be predicted as a browsing time zone, and a rule for downloading the acquired data Va first may be set.

  Further, in the embodiment, the information processing apparatus 1 automatically receives various information from the user terminal 2 and the like, and an example in which the browsing time zone is predicted based on the various information has been described. May be set.

  Further, the above-described embodiments can be appropriately combined as long as the processing contents are not inconsistent.

[8. effect〕
As described above, the information processing device 1 according to the embodiment includes the prediction unit 133 and the determination unit 134. The prediction unit 133 predicts a browsing time zone in which the user browses the content to be browsed. The determination unit 134 determines the acquisition data Va that the user terminal 2 acquires in advance based on the browsing time zone predicted by the prediction unit 133.

  Thereby, the information processing apparatus 1 can realize browsing of moving image content even in an environment where an optimal communication environment is not prepared.

  In the information processing apparatus 1 according to the embodiment, the prediction unit 133 predicts the browse content V to be browsed during the browse time zone.

  Thereby, the information processing apparatus 1 can realize browsing of the browsing content V that is a moving image content even in an environment where an optimal communication environment is not prepared.

  Further, in the information processing apparatus 1 according to the embodiment, the determining unit 134 determines a portion corresponding to the browsing time zone of the browsing content V as the acquisition data Va.

  Thereby, the data amount of the acquired data Va acquired in advance can be suppressed, so that the limited storage area of the user terminal 2 can be utilized without waste.

  Further, in the information processing device 1 according to the embodiment, the prediction unit 133 predicts the browse content V based on attribute information indicating a user attribute.

  Accordingly, the information processing apparatus 1 can predict the browsed content V even when the content is not browsed on the user terminal 2 at the time of prediction.

  In the information processing apparatus 1 according to the embodiment, the prediction unit 133 predicts, as the browse content V, the content being browsed by the user when performing the prediction.

  Thereby, the information processing apparatus 1 can cause the user terminal 2 to acquire in advance the content V1 having a high possibility of continuing to be browsed in the subsequent browsing time period as the browsed content V.

  Further, in the information processing apparatus 1 according to the embodiment, the prediction unit 133 predicts a browsing time zone based on a user's action history.

  Thereby, it is possible to predict the browsing time zone based on the usual action taken by the user.

  In the information processing apparatus 1 according to the embodiment, the prediction unit 133 predicts, as the viewing time zone, a time zone in which the user terminal 2 is not under the Wi-Fi communication environment and has a viewing history of the moving image content.

  This makes it possible to predict a time zone in which the need for buffering is considered to be high as a viewing time zone.

  In addition, the information processing apparatus 1 according to the embodiment further includes an instruction unit 135 that instructs the user terminal 2 to pre-acquire the acquired data determined by the determination unit 134, and the instruction unit 135 starts browsing the moving image content. It instructs the user terminal 2 to pre-acquire the acquired data from the point in time.

  This allows sufficient time for buffering the moving image content, so that the moving image content can be browsed without any problem even in an environment where an optimal communication environment is not prepared.

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

  Further, the “section (section, module, unit)” described above can be read as “means”, “circuit”, or the like. For example, the prediction unit can be replaced with a prediction unit or a prediction circuit.

Reference Signs List 1 information processing device 2 user terminal 3 content distribution device 11 communication unit 12 storage unit 13 control unit 100 information processing system 121 learning data storage unit 122 model 131 reception unit 132 model creation unit 133 prediction unit 134 determination unit 135 instruction unit V browse content Va acquisition data

Claims (11)

A prediction unit that predicts a viewing time period during which the user views the content,
Based on the browsing time zone predicted by the prediction unit, a determination unit that determines the acquisition data to be pre-acquired by the user terminal,
An information processing apparatus comprising: The information processing apparatus according to claim 1, wherein the prediction unit predicts a browse content to be browsed during the browse time period. The determining unit includes:
The information processing apparatus according to claim 2, wherein a part corresponding to the browsing time zone in the browsing content is determined as the acquisition data. The prediction unit includes:
The information processing apparatus according to claim 2, wherein the browsing content is predicted based on attribute information indicating an attribute of the user. The information processing apparatus according to any one of claims 2 to 4, wherein the prediction unit predicts the content being browsed by the user as the browsed content when performing the prediction. The prediction unit includes:
The information processing apparatus according to any one of claims 1 to 5, wherein the browsing time zone is predicted based on an action history of the user. The prediction unit includes:
The information processing device according to any one of claims 1 to 5, wherein the browsing time zone is predicted based on information on an action schedule of the user. The prediction unit includes:
The information according to any one of claims 1 to 7, wherein the user terminal is not under a Wi-Fi communication environment, and predicts, as the browsing time period, a time period in which there is a browsing history of moving image content. Processing equipment. The acquisition data determined by the determination unit, further comprising an instruction unit for instructing the user terminal to obtain in advance from the time of starting to browse video content,
The information processing apparatus according to any one of claims 1 to 8, wherein the instruction unit instructs the user terminal to pre-acquire the acquired data from a point in time when browsing of the moving image content is started. An information processing method executed by a computer,
A prediction step of predicting a viewing time period during which the user views the content;
Based on the browsing time zone predicted by the prediction step, a determining step of determining acquisition data to be pre-acquired by the user terminal,
An information processing method comprising: A prediction procedure for predicting a viewing time period during which the user views the content,
Based on the browsing time zone predicted by the prediction procedure, a determination procedure for determining acquisition data to be pre-acquired by the user terminal,
An information processing program for causing a computer to execute the following.

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