Information processing apparatus, information processing method, and computer program
阅读说明:本技术 信息处理设备和信息处理方法 (Information processing apparatus, information processing method, and computer program ) 是由 ***衣 于 2017-04-17 设计创作,主要内容包括:信息处理设备和信息处理方法。一种信息处理设备包括:接收单元,所述接收单元在再现视频期间从用户接收关于所述视频的预定操作;关联单元,所述关联单元将已接收操作与所述已接收操作在所述视频中被生成的再现时间关联;以及控制器,所述控制器控制按照时间序列显示与所述已接收操作关联的所述再现时间的重要度。(An information processing apparatus and an information processing method. An information processing apparatus includes: a receiving unit that receives a predetermined operation on a video from a user during reproduction of the video; an associating unit that associates a received operation with a reproduction time at which the received operation is generated in the video; and a controller that controls displaying the importance of the reproduction time associated with the received operation in time series.)
1. An information processing apparatus, the information processing apparatus comprising:
a receiving unit that receives a predetermined operation on a video from a user during reproduction of the video;
an associating unit that associates a received operation with a reproduction time at which the received operation is generated in the video; and
a controller that controls to display the importance of the reproduction time associated with the received operation in time series.
2. The information processing apparatus according to claim 1, wherein the controller updates the magnitude of the importance degree in response to a content of the received operation.
3. The information processing apparatus according to one of claims 1 and 2, wherein the receiving unit receives operations of a plurality of different viewers with respect to the video,
wherein the associating unit associates the received operation with the reproduction time at which the received operation was generated in the video on a per viewer basis, and
wherein the controller sets the importance level at the reproduction time associated with the received operation based on each viewer in response to the received operation, and performs importance level update by accumulating the importance levels set for each viewer.
4. The information processing apparatus according to claim 3, wherein the controller sets a weighting coefficient of the importance degree for each viewer who has performed the received operation.
5. The information processing apparatus according to one of claims 1 and 2, wherein the controller sets a weighting coefficient for each viewing period of the video serving as a target of the received operation.
6. The information processing apparatus according to claim 3, wherein the controller sets a weighting coefficient for each viewing period of the video serving as a target of the received operation.
7. The information processing apparatus according to claim 4, wherein the controller sets a weighting coefficient for each viewing period of the video serving as a target of the received operation.
8. An information processing method, comprising the steps of:
receiving a predetermined operation with respect to a video from a user during reproduction of the video;
associating a received operation with a reproduction time at which the received operation was generated in the video; and
control to display the importance of the reproduction time associated with the received operation in time series.
Technical Field
The invention relates to an information processing apparatus and an information processing method.
Background
Japanese unexamined patent application publication No. 2011-118292 discloses an electronic learning system. In the disclosed e-learning system, a management server, a video server, and a plurality of participant terminal devices are interconnected via the internet. When the management server sends a transfer command to the video server, the video server transfers video data to the plurality of participant terminal devices and causes the participant terminal devices to display the received video data. The electronic learning system thereby educates the participants who respectively watch the participant terminal devices.
Japanese unexamined patent application publication No. 2014-142586 discloses a test drive electronic learning system. In the disclosed test-driven e-learning system, video data for lectures is transmitted to a terminal device via a network. After the video data is transmitted to the terminal device, the test question data is transmitted to the terminal device.
A viewer who is a participant in a lecture can reproduce and view video provided in video data or moving image data. In the related art, it is difficult for the sender side that provides the video to identify the scene of the video in which the viewer is interested (the scene that the viewer considers to be valuable).
Disclosure of Invention
The purpose of the present invention is to help the user identify the importance of each scene in the video.
According to a first aspect of the present invention, there is provided an information processing apparatus. The information processing apparatus includes: a receiving unit that receives a predetermined operation with respect to a video during or after reproduction of the video; an associating unit that associates the received operation with a reproduction position in the video at which the received operation was generated; and a setting unit that sets the importance of the reproduction position associated with the received operation in response to the received operation.
According to a second aspect of the present invention, in view of the first aspect, the setting unit updates the magnitude of the importance degree in response to the content of the received operation.
According to a third aspect of the present invention, in view of one of the first and second aspects, the receiving unit receives operations of a plurality of different viewers with respect to the video. The association unit associates the received operation with the reproduction position generated in the video by the received operation on a per viewer basis. The setting unit sets the importance level at the reproduction position associated with the received operation on a per viewer basis in response to the received operation, and performs importance level update by accumulating the importance levels set for each viewer.
According to a fourth aspect of the present invention, in view of the third aspect, the setting unit sets a weighting coefficient of the importance degree for each viewer who performs the received operation.
According to a fifth aspect of the present invention, in view of one of the first to fourth aspects, the setting unit sets a weighting coefficient for each viewing period of the video serving as a target of the received operation.
According to a sixth aspect of the present invention, there is provided an information processing method. The information processing method includes: receiving a predetermined operation with respect to a video during or after reproduction of the video; associating the received operation with a reproduction location in the video at which the received operation was generated; and setting an importance of the reproduction position associated with the received operation in response to the received operation.
According to the first aspect of the present invention, the user can recognize the importance of each picture in the video.
According to the second aspect of the present invention, the accuracy of the obtained importance can be improved.
According to the third aspect of the present invention, the accuracy of the obtained importance can be improved.
According to the fourth aspect of the present invention, the accuracy of the obtained importance can be improved.
According to the fifth aspect of the present invention, the accuracy of the obtained importance can be improved.
According to the sixth aspect of the present invention, the user can recognize the importance of each picture in the video.
Drawings
Exemplary embodiments of the invention will be described in detail based on the following drawings, in which:
FIG. 1 generally illustrates the construction of an e-learning system of an exemplary embodiment;
FIG. 2 illustrates a hardware configuration of a computer;
FIG. 3 is a functional block diagram of an e-learning system;
FIG. 4 illustrates a video management table;
FIG. 5 illustrates a User Interface (UI) screen presented on a participant terminal device;
FIG. 6 is a flowchart illustrating an importance generation process;
FIG. 7 is a flowchart (subroutine) of a personal interestingness generation process;
FIG. 8 illustrates an interest coefficient management table;
fig. 9A to 9F illustrate examples of transition of personal interestingness and importance;
FIG. 10 illustrates an example of an importance file and a time bar for importance;
FIG. 11 illustrates an example of a time bar image; and
fig. 12A and 12B illustrate weighting coefficient management tables.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings.
Fig. 1 generally illustrates the configuration of an
The
Each of the participant
The
The
In the
Fig. 2 illustrates a hardware configuration of the
The
Fig. 3 is a functional block diagram of the
The
The
The
Fig. 4 illustrates a video management table used by the
The video management table of fig. 4 registers "video data". The video data is associated with a title of a lecture video (referred to as a video title) of the video content, a file path of the lecture video (referred to as a video file path), a file path of an index file including an index of the lecture video (referred to as an index file path), and a file path of an importance file including the importance of the lecture video (referred to as an importance file path). In the
In the example of fig. 4, "biological profile" and "physics profile" are registered as lecture content on the video management table. The "biological profile" registered as the video data includes three pieces of video data including a "biological profile (first utterance)", "biological profile (second utterance)", and "biological profile (third utterance)". The "physics profile" registered as the video data includes three pieces of video data including the "physics profile (first utterance)", "physics profile (second utterance)", and "physics profile (third utterance)". For example, in "biology overview (first talk)", the video file path is set to "C: $ movie $ biologi 1. wmv", the index file path is set to "C: $ index $ biologi 1. txt", and the importance file path is set to "C: $ import $ biologi 1. dat".
Fig. 5 illustrates a User Interface (UI)
The
In the
The
The
The video
The
While the lecture video is displayed on the
While the lecture video is displayed on the
The test
The importance generation process to be executed by the
Fig. 6 is a flowchart illustrating the importance level generation process. The following discussion is based on the premise of the viewing (listening) importance generation process by the participant on the
In the process of fig. 6, the
If the result of the determination in step S10 is affirmative (yes), the operation recording unit 22 starts recording about the operation acquired from the operation acquisition unit 12 in the
If the result of the determination in step S30 is non-affirmative (no), the operation recording unit 22 determines whether an operation regarding the end of reproduction of the lecture video has been received from the operation acquiring unit 12 in the
If the result of the determination at step S50 is affirmative (yes), the operation recording unit 22 ends the recording of the operation related to the lecture video acquired from the operation acquiring unit 12 in the
Fig. 7 is a flowchart (subroutine) illustrating the generation processing of the personal interestingness illustrated in step S40 of fig. 6.
In the process of fig. 7, the personal interest level generating unit 23 acquires the type of operation (hereinafter referred to as operation type) of the lecture video received in step S30 (step S41). The operation types are described in detail below.
The personal interest level generating unit 23 acquires the generation time of the operation of the intercom video received in step S30 (step S42). The generation time of the operation acquired in step S42 is not the current time, but the reproduction time of the operation on the target lecture video has already been generated.
The personal interest level generating unit 23 detects the generation timing of the operation of the intercom video received in step S30 (step S43). The generation timing of the operation is during reproduction of the target lecture video or after reproduction (after test).
The personal interestingness generating unit 23 acquires the interest coefficient corresponding to the operation type acquired in step S41 from the interest coefficient storage unit 24 (step S44). The personal interestingness generating unit 23 generates a personal interestingness regarding the lecture video by associating the generation time of the operation acquired in step S42 with the interest coefficient acquired in step S44 with respect to the lecture video, and performs personal interestingness update (step S45). The subroutine of the personal interestingness generation process thus ends. The process returns to step S30 of fig. 6 to continue the process.
Fig. 8 illustrates an interest coefficient management table used by the
The interest coefficient management table of fig. 8 stores "interest coefficient data" associated with an operation type corresponding to a lecture video to be reproduced, a generation timing of the operation, an interest coefficient set for the operation, and an influence time set for the generation time of the operation. In the
In the example of fig. 8, the operation type column lists "note", "favorite", "test", and "reproduction". The operation type "note" means that the note
Regarding the operation type "note", the generation time column lists "in video viewing", the interest coefficient column lists "+ 2", and the influence time column lists "
Regarding the operation type "favorite", the generation time column lists "in video viewing", the interest coefficient column lists "+ 1", and the influence time column lists "duration of 3 seconds before and after the time when favorite is set". The interest coefficient of the operation type "favorite" is set to "+ 1" for the following reason. The participant sets the favorite lecture video by clicking the favorite
Regarding the operation type "test", the generation time column lists "in video viewing", the interest coefficient column lists "-3", and the influence time column lists "after the viewing time when the lecture is transitioned to the test". The interest coefficient of the operation type "test" is set to "-3" for the following reason. The participant performs the test by clicking the test
Regarding the operation type "reproduction", the generation time column lists "after test", the interest coefficient column lists "+ 1", and the influence time column lists "time at the start of reproduction". The interest coefficient of the operation type "reproduction" is set to "+ 1" for the following reason. The participant reproduces the lecture video corresponding to the test by clicking the reproduction button of the video
Four operation examples are described herein as operation types. The operation type is not limited to these examples, and may include another example. The interest coefficients are not limited to those listed in fig. 8, and the administrator may change the operation type.
The importance generation process (and the personal interestingness generation process as a subroutine) of the exemplary embodiment are described using specific examples. The
Fig. 9A to 9F illustrate examples of transition of personal interestingness and importance. Fig. 9A illustrates the personal interestingness of the participant X who has viewed the "biological profile (first utterance)", and fig. 9B illustrates the importance of the "biological profile (first utterance)" obtained from the personal interestingness of the participant X. Fig. 9C illustrates the personal interestingness of participant Y who has viewed the "biological profile (first utterance)" subsequent to participant X, and fig. 9D illustrates the importance of the "biological profile (first utterance)" obtained from the personal interestingness of participants X and Y. Fig. 9E illustrates the personal interestingness of participant Z who has viewed the "biological profile (first lecture)" subsequent to participants X and Y, and fig. 9F illustrates the importance of the "biological profile (first lecture)" derived from the personal interestingness of participants X, Y and Z. The horizontal axis of each of fig. 9A to 9F represents the reproduction time t of lecture video ("biology profile (first lecture)"), the vertical axis of each of fig. 9A, 9C, and 9E represents the personal interestingness, and the vertical axis of each of fig. 9B, 9D, and 9F represents the importance. The discussion of the weighting coefficients is omitted here.
Participant X can now watch the lecture video "biological profile (first lecture)" on the
The importance is generated using the personal interestingness of participant X. Since no participant viewed the "biological profile (first lecture)" before participant X in this example, the newly gained importance is the personal interestingness of participant X. As illustrated in fig. 9B, the interestingness is +1 in the reproduction period of 0:22 to 0:28, is +2 in the reproduction period of 1:17 to 1:23, and is ± 0 in the remaining reproduction time.
Then, the participant X watches the lecture video "biological profile (first lecture)" on the
The importance degree update is performed using the importance degree generated from the personal interest degree of the participant X and the newly obtained personal interest degree of the participant Y. More specifically, the importance level update is performed by adding the personal interestingness of the participant Y to the generated personal interestingness. As illustrated in fig. 9D, the reproduction time period of the interestingness at 0:22 to 0:28, the reproduction time period at 1:32 to 1:38, and the reproduction time period at 2:07 to 2:13 are +1, the reproduction time period at 1:17 to 1:23 is +3, and the remaining reproduction time is ± 0.
Then, the participant Z watches the lecture video "biological profile (first lecture)" on the
The importance degree update is performed according to the importance degree generated based on the personal interests of the participants X and Y and the newly obtained personal interest degree of the participant Z. More specifically, the importance level update is performed by adding the personal interestingness of the participant Z to the previously generated personal interestingness. Referring to fig. 9F, the reproduction period of the interestingness from 0:22 to 0:28 and the reproduction period from 1:32 to 1:38 are + 1. The reproduction period of interest is +3 at 1:17 to 1:23, is-3 at 2:05 to 2:07 and 2:13 to 3:00, and is-2 at 2:07 to 2: 13. The interestingness is ± 0 at the remaining reproduction time.
Each time a participant watches a lecture video "biological profile (first lecture)", the personal interestingness of the participant is generated, and the importance is updated using the obtained personal interestingness. In this way, the number of participants contributing to the importance increases.
Fig. 10 illustrates an example of the importance file and the time bar of the importance thus obtained. The upper part of fig. 10 is a graph of an example of the importance file, and the lower part of fig. 10 illustrates an example of a time bar of the importance generated by the importance notifying unit 27 (see fig. 3) based on the importance file illustrated in the upper part of fig. 10. The horizontal axis of each of the upper and lower parts of fig. 10 represents the reproduction time t of the lecture video (here, "biological profile (first lecture)"), and the vertical axis of the upper part of fig. 10 represents the importance. The entire reproduction period of the lecture video "biological profile (first lecture)" is 3 minutes. The first minute is for the beginning of the lecture video, the second minute is for the explanation of a, and the third minute is for the explanation of B (see also fig. 5).
Referring to fig. 10, a first threshold Th1 and a second threshold Th2 larger than the first threshold are set with respect to the importance of the exemplary embodiment. The reproduction time period with the importance degree of 0:06 to 0:28 and the reproduction time period of 1:14 to 1:45 are higher than the
According to the importance level file illustrated in the upper part of fig. 10, the time bars of importance levels illustrated in the lower part of fig. 10 are segmented into green periods having importance levels higher than the first threshold Th1, red periods having importance levels lower than the second threshold Th2, and yellow periods having importance levels falling between the first threshold Th1 and the second threshold T2. The time bar of importance of the exemplary embodiment is thus generated based on the importance file (i.e., the time distribution of importance) and the first threshold Th1 and the second threshold Th2 set with respect to the importance.
Fig. 11 illustrates an example of a time bar image of importance. The time bar image of the importance is generated by the importance notifying unit 27 in the
The time bar image includes a check box on its leftmost side, a thumbnail (still image) set to the right of the check box and being a characteristic of the lecture video "biology profile (first lecture)", a time bar on the right of the thumbnail, and an update date on the right of the time bar. The administrator using the
Fig. 12A and 12B illustrate weighting coefficient management tables. Fig. 12A illustrates weighting coefficients set for participants individually. Fig. 12B illustrates weighting coefficients respectively set for the lecture attendance periods of the participant talkback video. The weighting coefficient management table is stored on the weighting coefficient storage unit 26 (see fig. 3) in the
Referring to fig. 12A, participants having relatively higher scores are weighted with higher weighting coefficients, and participants having relatively lower scores are weighted with lower weighting coefficients. In this example, the score of the participant becomes lower in the order of participant X, participant Y, and participant Z. The weighting coefficients for participant X, participant Y and participant Z are 2.0, 1.0 and 0.5, respectively.
In the importance level generation process of fig. 6, the importance level generation unit 25 generates (changes) the personal interest level using the weighting coefficient of the participant who watches the lecture video. By multiplying the original value by a weighting factor of 2.0, participant X has a personal interest level that is 2 times the original value. The personal interestingness of participant Y is equal to the original value by multiplying the original value by a weighting factor of 1.0. By multiplying the original value by a weighting factor of 0.5, the personal interest level of the participant Z is half of the original value. As a result, the importance degrees obtained from the three persons of the participants X, Y and Z who have viewed the lecture video reflect the above-described weighting coefficients. More specifically, the personal interestingness of a participant having a relatively high score is more reflected in the personal interestingness than the personal interestingness of a participant having a relatively low score.
The weighting coefficients of the participants are set according to the relative scores of the participants. The method of determining the weighting coefficients is not limited to this method. For example, the weighting coefficients of the participants may be set according to the attendance rates of the participants to the lecture. Alternatively, the weighting coefficients of the participants may be set according to a combination of the relative scores and the attendance rates of the participants.
Referring to fig. 12B, a participant who watches relatively early after the lecture video is publicly disclosed to each participant (after the lecture video is registered on the server apparatus 20) is weighted with a higher weighting coefficient, and a participant who watches relatively late is weighted with a lower weighting coefficient. In this example, a participant who watches the lecture video within one week from the public disclosure is weighted with a weighting coefficient of 2.0, a participant who watches the lecture video within one week to one month from the public disclosure is weighted with a weighting coefficient of 1.5, and a participant who watches the lecture video one month or more later than the public disclosure is weighted with a weighting coefficient of 1.0.
In the importance level generation process of fig. 6, the importance level generation unit 25 generates (changes) the personal interest level using the weighting coefficient of the lecture attendance period of the participant who watches the lecture video. The personal interestingness of a participant (e.g., participant X) viewed within one week from the public disclosure is twice the original interestingness by multiplying the original interestingness by the weighting factor 2.0 for the lecture attendance period. By multiplying the original interestingness by the weighting factor 1.5 for the lecture attendance period, the personal interestingness of the participant (e.g., participant Y) viewed within one week to one month from the public disclosure is 1.5 times the original interestingness. The personal interestingness of a participant (e.g., participant Z) who watches the lecture video from a month or more later than the publicly disclosed one is equal to the original interestingness by multiplying the original interestingness by the weighting coefficient of the lecture attendance period of 1.0. The importance of the three persons (i.e., participants X, Y and Z) reflects the weighting coefficients in this manner. More specifically, the personal interestingness of the participant who watches the lecture video earlier is reflected more in importance than the personal interestingness of the participant who watches the lecture video later.
In the above discussion, the weight management table of fig. 12A and the weight management table of fig. 12B are used separately. The exemplary embodiments are not limited to this method. A plurality of weighting tables (such as the two tables of fig. 12A and 12B) having different settings may be used in combination.
The foregoing description of the exemplary embodiments of the invention has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed. It is evident that many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to understand the invention for various embodiments and with the various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the following claims and their equivalents.
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