JP2018092324A - Content identification device and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a content identification device and a program for identifying content which is identical to content that a user requests.SOLUTION: A content identification device obtains meta data which is data representing a feature of content accompanying the content for a plurality of pieces of content, and comprises meta data management means for accumulating the meta data while classifying the meta data by a type of the meta data, similarity calculation means for calculating similarity between pieces of the meta data for each type of the meta data accumulated, degree of equivalence calculation means for calculating a degree of equivalence between the content and another content other than the content on the basis of the similarity calculated by the similarity calculation means, and list creation means for creating a list of meta data including an acquiring method of content which is specified as content identical to the specified content on the basis of the degree of equivalence of pieces of the content calculated by the degree of equivalence calculation means.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a content identification device and a program for specifying content that can be regarded as identical or identical.

  In recent years, various businesses have provided various contents. Along with this, there are various ways of providing content. For example, providing methods such as terrestrial broadcasting, satellite broadcasting, and Internet distribution are used for each business operator. For this reason, the number of contents provided to the user is enormous.

  Therefore, technology development for facilitating selection of content by the user is underway. An example of such a technique is disclosed in Patent Document 1.

In the technique disclosed in Patent Document 1, another program related to this program is specified based on what the recorded program (that is, the program in which the user is interested) recorded by the user is. And it thinks that a user is interested also about this specified other program, and displays information about this specified other program on the television screen as recommendation information.
The user can easily select a program that the user is interested in by referring to the recommendation information.

JP, 2006-178861, A

  By using a recommendation technique or the like as disclosed in Patent Document 1, the user can easily select a program in which the user is interested. However, the technique disclosed in Patent Document 1 cannot solve the problems described below. This problem will be described.

  Currently, the same content may be distributed on different media. For example, after a certain program is broadcast on the ground, the same program may be distributed over the Internet. In this case, the user needs to properly use various devices and applications such as a television, a personal computer, and a smartphone in order to acquire desired content.

However, the user may not know that the same content is distributed on different media. Also, even if an acquisition method for a certain medium is known, the acquisition method is not necessarily optimal for the user's situation and device function, and there may be other acquisition methods more suitable for the user. possible.
Therefore, when the same content as the content desired by the user can be acquired by other methods, it is desired to present each of the acquisition methods to the user.

  However, the technique disclosed in Patent Literature 1 presents a program related to a program recorded by the user in the past to the user, and is not a technique for presenting information about the same program as the user desires. That is, it is not a technique for identifying the same content.

  In the first place, the technique disclosed in Patent Document 1 presents a program selected from programs that can be received by the currently used television, and does not consider programs that can be received by other devices. . In other words, no consideration is given to programs that can be received by devices other than the currently used television.

  Therefore, in a general technique such as the technique disclosed in Patent Document 1, even when the same content is distributed on different media, information related to the same content as the content desired by the user is presented. I could not do anything.

  Therefore, an object of the present invention is to provide a content identification device and a program capable of specifying the same content in order to present information related to the same content as the content desired by the user, for example.

  The content identification device according to the present invention acquires, for each of a plurality of contents, metadata that is data indicating the characteristics of the content attached to the content based on a predetermined metadata acquisition method, and the acquired metadata is Metadata management means for classifying and storing each metadata type, similarity calculation means for calculating the similarity between the metadata for each metadata type stored by the metadata management means, and Based on the similarity calculated by the similarity calculation means, the sameness calculation means for calculating the sameness between the content and other content other than the content, and the sameness between the contents calculated by the identity calculation means Based on a list of metadata that includes content acquisition methods identified as the same content as the specified content It includes a list creation means for growth.

  In the content identification device according to the present invention, when the list creation unit receives a list request including content specification from a user, the list is generated based on the identity of the content calculated by the identity calculation unit. A content identification device that creates a list of metadata including a content acquisition method specified as the same content as the content specified by the request, and outputs the created list to the user as a response to the list request It is good.

  In the content identification apparatus according to the present invention, the degree-of-identity calculation unit assigns different weights depending on the type of the metadata to the degrees of similarity between the metadata calculated by the degree-of-similarity calculation unit, and the degree-of-identity calculation unit The content identification device may calculate the degree of identity between the contents based on a value obtained by adding the similarities of the metadata given the weights in units of contents.

  In the content identification device according to the present invention, the degree-of-identity calculation means includes a plurality of degree-of-identity calculation units for calculating the degree of identity between the contents. Each of the calculation units may be a content identification device that calculates the degree of identity between the contents by different calculation methods.

  The content identification apparatus according to the present invention further includes content combination management means, and the similarity calculation means is configured to store each metadata between any of the metadata types managed by the metadata management means. The similarity is calculated, and the combination of contents corresponding to each metadata whose calculated similarity is equal to or higher than a predetermined standard is stored in the content combination management unit and not stored in the content combination management unit As for the combination of contents, a content identification apparatus that does not perform the calculation of the similarity between the metadata by the similarity calculation unit and the calculation of the degree of identity between the contents by the identity calculation unit.

  The program according to the present invention causes a computer to function as the content identification device according to the present invention.

  According to the content identification device and the program according to the present invention, for example, in order to present information related to the same content as the content desired by the user, the same content can be specified.

It is a functional block diagram showing the basic composition of the 1st embodiment of the present invention. It is a flowchart showing the basic operation | movement of the 1st Embodiment of this invention. It is a functional block diagram showing the basic composition of the 2nd Embodiment of this invention. It is a flowchart showing the basic operation | movement of the 2nd Embodiment of this invention. It is a functional block diagram showing the fundamental structure of the 3rd Embodiment of this invention. It is a figure (1/4) showing an example of the data in the Example of this invention. It is a figure (2/4) showing an example of the data in the Example of this invention. It is a figure (3/4) showing an example of the data in the Example of this invention. It is a figure (4/4) showing an example of the data in the Example of this invention.

  First, an outline of an embodiment of the present invention will be described. In the embodiment of the present invention, when the same content is provided by various companies on different media, the same content is identified using the metadata of the contents held by each company. is there.

  As described above, in this embodiment, since the same content can be identified, when a request for content that the user wants to earn is received, a list of metadata including a method for acquiring the content that is identified as the content is returned. be able to.

That is, from the viewpoint of the user, it is possible to acquire a list of metadata including the content acquisition method simply by inputting information about the content that the user wants to acquire into the system. The user can select a content acquisition method suitable for his / her situation and device function from the list. Thus, the user can acquire the content by the selected acquisition method and enjoy the content.
The above is the outline of this embodiment.

  Next, embodiments of the present invention will be described in detail with reference to the drawings. In the following, three embodiments will be described. Here, the first embodiment is a basic embodiment. The second embodiment is an embodiment in which the configuration of the first embodiment is simplified. Further, the third embodiment is an embodiment in which the first embodiment can be modified to reduce the calculation amount.

<First Embodiment>
As shown in FIG. 1, the content identification apparatus 101 according to the first embodiment includes a metadata management unit 10, a metadata similarity management unit 20, a content identity management unit 30, and a content acquisition method list creation unit 40. Including. Each device is connected to a network such as a local area network (LAN) or the Internet, and can communicate with each other. In the following description and drawings, the database is appropriately expressed as “DB”.

  The metadata management means 10 is a device that acquires and manages information (hereinafter referred to as “metadata”) related to each provided content from a provider that provides the content.

The metadata management unit 10 includes a metadata shaping unit 11 and a metadata management DB 12. The metadata shaping unit 11 acquires metadata by communicating with a terminal (not shown) used by each business operator. The metadata shaping unit 11 stores the acquired metadata in the metadata management DB 12 for each type of metadata. The metadata management DB 12 is a storage device and stores metadata for each type of metadata.

  The metadata similarity management unit 20 is a device that calculates and manages “metadata similarity”, which is the degree of similarity between metadata managed by the metadata management unit 10.

  The metadata similarity management unit 20 includes n (n is an arbitrary natural number) metadata similarity calculation units 21 and a metadata similarity management DB 22. The number of metadata similarity calculation units 21 is provided according to the type of metadata. Each of the metadata similarity calculation units 21 calculates the metadata similarity by comparing the same type of metadata, and stores the calculated metadata similarity in the metadata similarity management DB 22. The metadata similarity management DB 22 is a storage device, and stores the metadata similarity for each type of metadata.

  Further, the content identity management means 30 calculates “content identity”, which is the degree of identity between contents corresponding to metadata, based on the metadata similarity managed by the metadata similarity management means 20. It is a device to manage.

  The content identity management unit 30 includes m (m is an arbitrary natural number) content identity calculation units 31 and a content identity management DB 32. The content identity calculation units 31 are provided in a number corresponding to the number of content identity calculation methods. Then, each of the content identity calculation units 31 calculates the content identity by a calculation method corresponding to the content identity calculation unit 31 itself, and stores the calculated content identity in the content identity management DB 32. The content identity management DB 32 is a storage device, and stores the content identity calculated by each content identity calculation unit 31.

Further, the content acquisition method list creation unit 40 includes a content acquisition method list creation unit 41. The content acquisition method list creation unit 41 accepts a metadata list creation request including a content acquisition method identical to the content desired to be used from a user who desires to use the content. This creation request includes specification of content desired to be used.
The content acquisition method list creation unit 41 that has received this request creates a metadata list that includes the same content acquisition method as the specified content, based on the content identity managed by the content identity management means 30. . In addition, the content acquisition method list creation unit 41 outputs the created list to the user. Here, the user is a user who uses content, for example, a user who wants to watch a television program that is one of the content.

  The content acquisition method list creation unit 41 receives a creation request and outputs a list by communicating with a terminal (not shown) used by the user. The user can view the content by selecting a content acquisition method suitable for his / her situation by referring to the list on the terminal used by the user.

  The content identification device 101 can be realized by incorporating software specific to the present embodiment into a general server device or personal computer.

  More specifically, the content identification device 101 includes an arithmetic processing device such as a CPU (Central Processing Unit). The content identification device 101 is temporarily required when an auxiliary storage device such as a hard disk drive (HDD) or a solid state drive (SSD) that stores various programs or an arithmetic processing device executes the program. A main memory such as a RAM (Random Access Memory) for storing data.

In the content identification apparatus 101, the arithmetic processing device reads various programs from the auxiliary storage device, and performs arithmetic processing based on these various programs while developing the read various programs in the main storage device.
Then, by controlling the hardware of each device based on this calculation result, the above-described means (metadata management means 10, metadata similarity management means 20, content identity management means 30, and content acquisition method list) Creating means 40). That is, this embodiment can be realized by cooperation of hardware and software.
Note that each of the metadata management unit 10, the metadata similarity management unit 20, the content identity management unit 30, and the content acquisition method list creation unit 40 may be realized by separate devices. And a content identification system may be comprised by each apparatus which implement | achieves these means cooperating.

  Next, the operation of this embodiment will be described with reference to the sequence diagram of FIG. As a premise, in this example, the first content provided by the operator A (shown as “circled number 1” in the figure. Other contents are also shown in the figure by circled numbers). The second content provided by the operator A and the fourth content provided by the operator C are the same video and audio content. That is, it is assumed that the content is the same.

  In addition, it is assumed that the third content provided by the operator B is content related to the first content, the second content, and the fourth content. Furthermore, it is assumed that the fifth content provided by the operator C is content not related to the first content, the second content, and the fourth content.

  First, in step S <b> 1, the metadata shaping unit 11 acquires metadata of content held by each business operator. Here, what kind of metadata is included differs depending on the content and the business. Therefore, the metadata shaping unit 11 shapes each metadata so that it can be easily compared, and registers the metadata in the metadata management DB 12. More specifically, a plurality of metadata included in metadata corresponding to one content is classified into metadata one by one and classified for each metadata of the same type.

For example, if the classified metadata is metadata representing the title of the content, the metadata is classified into a metadata type “title”. In addition, if the classified metadata is metadata that represents an outline of the content, it is classified into a metadata type “summary”.
In step S2, the metadata shaping unit 11 stores the shaped metadata thus shaped in the metadata management DB 12.

In step S3, each of the n metadata similarity calculators 21 (only one metadata similarity calculator 21 is shown in the figure) makes an inquiry to the metadata management DB 12. In the figure, it is described that step S3 is continuously executed with the end of step S2. However, this is merely an example, and step S3 may be continuously performed with the end of step S2 as an opportunity, or step S3 may not be continuously performed with the end of step S2.
For example, the metadata similarity calculation unit 21 may be notified that metadata has been accumulated in the metadata management DB 12. In this case, since the metadata similarity calculation unit 21 performs step S3 with this notification as a trigger, step S3 is continuously executed with the end of step S2.
On the other hand, a configuration in which the metadata similarity calculation unit 21 periodically performs step S3 or a configuration in which step S3 is performed when there is an acquisition request for a content acquisition method list from the user may be employed. In this case, step S3 is not executed with the end of step S2.
That is, the description in the drawing is for convenience of illustration, and does not limit the configuration of the present embodiment.
In step S4, the formatted metadata is acquired as the response. Then, each of the n metadata similarity calculation units 21 compares the acquired metadata with each other, calculates a metadata similarity that is a degree of similarity, and registers it in the metadata similarity management DB 22. Note that the n metadata similarity calculation units 21 have different types of metadata for which the metadata similarity is calculated.

  For example, the metadata similarity calculation unit 21-2 calculates the metadata similarity for the type of metadata “title” of each content. Further, for example, the metadata similarity calculating unit 21-3 calculates the metadata similarity for the metadata of the type “summary” of each content.

  Next, in step S5, each of the n metadata similarity calculation units 21 calculates the metadata similarity for all the combinations of contents stored in the metadata management DB 12, and the calculation result is the metadata similarity. Store in the management DB 22. The storage method is arbitrary, but for example, a table in which identifiers of contents are arranged in vertical columns and horizontal rows is created, and the corresponding content metadata is created at the intersection of the rows and columns of the table. Stores the metadata similarity of. Note that details of such a storage method will be described with reference to FIG.

In step S6, each of the m content identity calculation units 31 (only one content identity calculation unit 31 is illustrated in the drawing) makes an inquiry to the metadata similarity management DB 22. In step S7, the metadata similarity calculated by the n metadata similarity calculators 21 is acquired as a response.
In the drawing, for the sake of convenience, it is described that step S6 is continuously executed with the end of step S5 as a trigger. However, this is merely an example, and step S6 may be continuously performed with the end of step S5 as a trigger, or step S6 may not be continuously performed with the end of step S5 as a trigger.
For example, the content similarity calculation unit 31 may be notified that metadata has been accumulated in the metadata similarity management DB. In this case, since the content identity calculation unit 31 performs step S6 with this notification as a trigger, step S6 is continuously executed with the end of step S5 as a trigger.
On the other hand, a configuration in which the content identity calculation unit 31 periodically performs step S6 or a configuration in which step S6 is performed when there is a content acquisition method list acquisition request from the user may be employed. In this case, step S6 is not executed in response to the end of step S5.
That is, the description in the drawing is for convenience of illustration, and does not limit the configuration of the present embodiment.

  Then, each of the m content identity calculation units 31 compares the acquired metadata similarities, and calculates the content identity that is the degree of identity between the contents corresponding to the compared metadata similarities. Are registered in the content identity management DB 32. Note that the m content identity calculation units 31 have different content identity calculation methods.

  For example, the content identity calculation unit 31-1 calculates the content identity by placing emphasis on the metadata similarity of the type of metadata “title”. On the other hand, the content identity calculation unit 31-2 calculates the content identity with an emphasis on the metadata similarity of the metadata of the type “summary”. Also, in some cases, the metadata similarity weight is set so that the degree of identity increases only when the content video and audio content completely match. In addition, the same degree is also applied to the highlight and digest versions. In some cases, the metadata similarity is set so as to have a higher weight.

  In step S8, each of the m content identity calculation units 31 calculates content similarity for all combinations of content corresponding to the metadata similarity stored in the metadata similarity management DB 22. The result is stored in the content identity management DB 32. Although the storage method is arbitrary, for example, a table is created in which identifiers for each content are arranged in vertical columns and horizontal rows, and the content of the corresponding content is shared at the intersection of the rows and columns of this table. Store once. The details of such a storage method will be described with reference to FIG. 6-4 in the description of an embodiment described later.

On the other hand, in step S <b> 9, the user transmits a metadata list creation request including the same content acquisition method as the content desired to be used to the content acquisition method list creation unit 41. This creation request includes specification of content desired to be used. Here, the content desired to be used is, for example, a program that the user desires to view. The designation of the content desired to be used is, for example, transmitting content specifying information for uniquely identifying the content desired to be used, as shown in the figure, and corresponds to, for example, the title of the content. Sending text data, URL corresponding to the content, and the like.
In the drawing, for the sake of convenience, it is described that step S9 is continuously executed in response to the end of step S8. However, the user can execute step S9 at a timing desired by the user regardless of the timing at which step S8 ends. That is, the description in the drawing is for convenience of illustration, and does not limit the configuration of the present embodiment.

  In step S <b> 10, the content acquisition method list creation unit 41 makes an inquiry to the metadata management DB 12 using the content specifying information. Further, in step S11, it is resolved which content is the specific content corresponding to the content specifying information. For example, if the content corresponding to the content specifying information is the first content, it is determined that the content corresponding to the content specifying information is the first content by making an inquiry to the metadata management DB 12. Solve.

  Next, in step S12, the content acquisition method list creation unit 41 makes an inquiry to the content identity management DB 32. In step S13, the content identity calculated by any content identity calculator 31 is acquired as a response. Which content identity calculation unit 31 uses the calculation result is determined in consideration of the user's wishes and the like. The user's desire includes, for example, whether or not it is desired that similar content is passed when a method for acquiring the content desired by the user is not found.

Then, the content acquisition method list creation unit 41 generates a content acquisition method list based on the acquired content identity. For example, a list is created by arranging content in descending order of content identity.
This list is composed of metadata including a method for acquiring each content. Specifically, if the content is content distributed on the Internet, for example, a URL for acquiring the content is included in the list as metadata. In addition, when the user refers to the list, the text data indicating the acquisition method, the text data indicating the broadcast time, the resolution, and the screen ratio are expressed so that each URL corresponds to what acquisition method. Text data or the like may also be included in the list.
Furthermore, if the content is broadcast on terrestrial waves, for example, the terrestrial channel and broadcast time may be included in the list as metadata instead of the URL.
If the number of contents included in the list becomes enormous, it becomes difficult for the user to select contents using the list. Therefore, it is preferable to set a threshold for the number of contents to be included in the list, and not to include content metadata exceeding the threshold in the content acquisition method list.

  In step S14, the content acquisition method list creation unit 41 passes the created content acquisition method list to the user. For example, the content acquisition method list is passed to the terminal used by the user. For example, if the content corresponding to the content specifying information is the first content, in addition to the first content, the second content and the fourth content that are the same content as the first content are included. Pass the content acquisition method list.

  The user can select the content acquisition method and view the content by referring to the list at the terminal used by the user.

According to the present embodiment described above, the same content as the content desired by the user can be specified by using the metadata. That is, the same content can be identified.
Thereby, when the same content is distributed by a plurality of media, it is possible to acquire the content in each media. In addition, since the user can refer to the list and refer to any acquisition method, it is possible to use an appropriate method according to the situation such as the type of device that the user owns and the time period when content is desired to be referred to. Content can be acquired.

  Furthermore, in the present embodiment, by preparing n metadata similarity calculation units 21, the metadata similarity can be calculated for each type of metadata. Therefore, it is possible to calculate the similarity of metadata more accurately than in the case of calculating the metadata similarity without considering the type of metadata.

  In the present embodiment, by preparing m content identity calculation units 31, the content identity can be calculated by different calculation methods. Then, for example, according to the user's desire or the like, it is possible to select which calculation method is used to use the content identity. Thereby, it is possible to create a list according to the user's request.

<Second Embodiment>
Next, the configuration of the second embodiment will be described with reference to FIG. Note that the basic configuration of the present embodiment is the same as that of the first embodiment. Therefore, in the following, the points peculiar to the present embodiment will be described in detail, and the overlapping description will be omitted for the parts common to the first embodiment.

  As shown in FIG. 3, the content identification apparatus 102 according to the second embodiment includes a metadata management unit 10, a similarity / identity management unit 50, and a content acquisition method list creation unit 40. The metadata management unit 10 and the content acquisition method list creation unit 40 are the same as those in the first embodiment. On the other hand, in the present embodiment, a similarity / identity management unit 50 is provided instead of the metadata similarity management unit 20 and the content identity management unit 30 of the first embodiment.

  The similarity / identity management unit 50 is a device having the functions of the metadata similarity management unit 20 and the content identity management unit 30. The similarity / identity management means 50 includes a similarity / identity calculation unit 51 and a content identity management DB 52.

  Then, the similarity / identity calculation unit 51 calculates the metadata similarity based on the shaped metadata stored in the metadata similarity management DB 22 and uses the calculated metadata similarity. Further, the degree of content identity is calculated. Further, the similarity / identity calculation unit 51 stores the calculated content identity in the content identity management DB 52.

  By adopting such a configuration, in this embodiment, it is not necessary to store metadata similarity for all metadata combinations. That is, it is not necessary to construct a database such as the metadata similarity management DB 22. Therefore, it is not necessary to prepare a storage device for constructing the metadata similarity management DB 22. Similarity / identity management means 50 is the same as the hardware of the content identification device 102, like the metadata management means 10, metadata similarity management means 20, content identity management means 30, and content acquisition method list creation means 40. This is realized through collaboration between software and software. Further, as described in the first embodiment, when each unit is realized by a separate device, the similarity / identity management unit 50 is realized by a device separate from a device that realizes other units. May be.

Next, the operation of the present embodiment will be described with reference to the sequence diagram of FIG.
First, steps S21 and S22 in FIG. 4 are the same as steps S1 and S2 in FIG.

  In step S23, each of the m similarity / identity calculating units 51 (only one similarity / identity calculating unit 51 is illustrated in the drawing) inquires of the metadata management DB 12. . In step S24, the formatted content is acquired as a response. Note that, similarly to step S3 of the first embodiment, step S23 may be continuously performed with the end of step S22 as a trigger, and step S23 is not continuously performed with the end of step S22 as a trigger. It is good also as a structure. That is, the description in the drawing is for convenience of illustration, and does not limit the configuration of the present embodiment.

  Then, each of the m similarity / identity calculation units 51 compares the acquired metadata with each other, and calculates a metadata similarity that is a degree of similarity. Such calculation of metadata is performed for all types of metadata. Then, each of the m similarity / identity calculation units 51 compares the calculated metadata similarities, and calculates the content identity that is the degree of identity between the contents corresponding to the compared metadata similarities. Calculate and register in the content identity management DB 52. The m similarity / identity calculation units 51 have different content identity calculation methods.

  For example, the similarity / identity calculation unit 51-1 calculates the content identity by weighting the metadata similarity of the type of metadata “title”. On the other hand, the content similarity is calculated with emphasis on the metadata similarity of the metadata of the type “summary” in the similarity / identity calculation unit 51-2.

  Next, in step S <b> 25, each of the m similarity / identity calculation units 51-1 calculates content similarity for all combinations of content, and stores the calculation result in the content identity management DB 52. The storage method may be the same as the content identity management DB 32 described above.

  Thereby, a database having the same content as the content identity management DB 32 of the first embodiment is constructed as the content identity management DB 52. The subsequent processing from step S26 to step S content identity calculation unit 31 is the same as the processing of step S9 and step S14 in FIG.

  The present embodiment described above has the same effect as the first embodiment. In the present embodiment, if the metadata similarity and the content identity are calculated for a certain content combination, it is not necessary to store the calculated metadata similarity. Therefore, there is an effect that it is not necessary to construct a database like the metadata similarity management DB 22.

  However, in the case of the configuration as in the present embodiment, the amount of calculation required for the entire system increases as compared with the first embodiment. For example, in the first embodiment, if the metadata similarity is calculated and held for each type of metadata of each content combination, the m content identity calculation units 31 The calculation result can be referred to. Therefore, it is not necessary for each of the m content identity calculation units 31 to calculate the metadata similarity each time the content identity is calculated.

  On the other hand, in this embodiment, each of the m content identity calculation units 31 needs to calculate the metadata similarity every time the content identity is calculated. Therefore, in the present embodiment, the amount of calculation required for the entire system increases compared to the first embodiment. However, since there is an effect that it is not necessary to construct a database such as the metadata similarity management DB 22 as described above, the first embodiment and the second embodiment according to the environment in which this embodiment is implemented. Any one of the above may be selected. That is, the first embodiment may be implemented if there is a margin in the capacity of the storage device, and the second embodiment may be implemented if there is a margin in the arithmetic processing capability.

<Third Embodiment>
Next, a third embodiment will be described. The basic configuration of this embodiment is the same as that of the first embodiment. Alternatively, the basic configuration of this embodiment may be the same as that of the second embodiment instead of the first embodiment.
In any case, in the following, the points specific to the present embodiment will be described in detail, and overlapping description of portions common to the first embodiment and the second embodiment will be omitted.

  In each of the above-described embodiments and this embodiment, the metadata similarity and the content identity are calculated and stored in the database for all content combinations provided by each business operator. For this reason, the amount of data managed by the metadata similarity management DB 22, the content identity management DB 32, or the content identity management DB 52 has increased in proportion to the square of the number of contents.

  Thus, since the search target increases as the amount of data increases, it takes time to identify the same content. As a matter of course, when the amount of data increases, a larger storage area is required.

However, there are about several identical contents that are actually distributed on different media. For example, when a certain content is broadcast on terrestrial waves and distributed on video on demand with some services, one content is distributed on about three media.
Therefore, even if the metadata similarity and content identity are calculated for all combinations of content such as thousands to tens of thousands, for example, the calculation result is more likely to be wasted.

  In view of this, the present embodiment limits combinations of content for which the metadata similarity and content identity are to be calculated based on a predetermined criterion. As a result, the amount of data managed in each database is reduced, the same content can be quickly identified, and a large storage area is not required.

In this example, as an example of a predetermined standard, the metadata similarity calculation unit 21-2 calculates metadata similarity for the type of metadata “title” of each content, and content whose metadata similarity is equal to or greater than a threshold value. Further, the metadata similarity and content identity are calculated only for the combination.
That is, for a combination of contents whose metadata similarity of the type “title” is less than the threshold, the metadata similarity of the type of metadata “title” is calculated, but other types of metadata are calculated. Do not calculate similarity or content identity.

For this purpose, in this embodiment, a content combination management DB 60 is provided as shown as the content identification device 103 in FIG. First, any metadata similarity calculation unit 21 calculates the metadata similarity only for any kind of metadata.
For example, the metadata similarity calculation unit 21-2 calculates the metadata similarity only for the metadata of the type “title” of each content. Then, based on the calculation result, only a combination of contents whose metadata similarity of the type of metadata “title” is equal to or greater than a threshold value is stored in the content combination management DB 60.
However, this method is merely an example, and the method for determining the content combination to be registered in the content combination management DB 60 is not limited to this. For example, a method of registering only a combination of contents whose similarity between “title” and “summary” exceeds a certain threshold value may be used. In addition, for example, a method of registering only a combination of contents in which a value obtained by adding weighting values to “title” and “summary” exceeds a certain threshold may be used.

  Then, the metadata similarity calculation unit 21 other than the metadata similarity calculation unit 21-2 targets only the combination of contents stored in the content combination management DB 60, and stores metadata of types other than “title”. The metadata similarity is calculated and stored in the metadata similarity management DB 22. The m content identity calculation units 31 calculate the content identity based on the metadata similarity stored in the metadata similarity management DB 22. That is, the metadata similarity calculation unit 21 other than the metadata similarity calculation unit 21-2 and the m content identity calculation units 31 do not calculate a combination of contents that are not stored in the content combination management DB 60. .

  With the configuration described above, the present embodiment limits the combinations of contents to be calculated, so that the amount of calculation for the entire system can be reduced. As a result, the amount of data managed in each database is reduced. Therefore, it is possible to quickly identify the same content and to make a large storage area unnecessary.

  In the present embodiment, as shown in FIG. 5, a calculation result reduction unit 70 may be further provided. The calculation result reduction unit 70 is a part that limits the number of contents included in the content acquisition method list. In the above description, it has been described that a list is created by arranging contents in descending order of content identity. However, if this is done, the number of contents included in the list becomes enormous. On the other hand, as described above, there are actually several (for example, three) identical contents. Therefore, it is not preferable to include more contents than necessary in the list.

Therefore, the calculation result reduction unit 70 prevents a predetermined number of contents from being included in the list. For example, for a certain content, the content identity of the content whose content identity is up to 5th is stored in the content identity management DB 32, but the content identity of content of 6th or less is deleted. To do.
By doing so, it is possible to limit the number of contents included in the content acquisition method list created by the content acquisition method list creation unit 41.

<Example>
The three embodiments have been described above. Next, more specific examples when these embodiments are implemented will be described as examples. This time, an example will be described based on the configuration corresponding to the first embodiment.

FIG. 6A illustrates an example of content metadata held by the operator A, the operator B, and the operator C. These pieces of information are information input to the metadata shaping unit 11.
The content of “title” is “** Story (5)”, “Continuous TV Drama ** Story (5)” and “5th ** Story October 18 broadcast” shown in FIG.・ The audio content is the same. “Title” is “a story that can be understood in 5 minutes” is a content related to the above-mentioned three contents, and “noon news broadcast on October 18” is a content that has nothing to do with the above-mentioned three contents. And

  Even if the content is the same, the type of content metadata may differ depending on the provider and the distribution media. For example, the metadata of “title” is “** Story (5)” is title, url, date, id, distributor, and the metadata of “5th ** Story October 18 broadcast” is title, url, distributor. Moreover, even if the metadata is the same content and the same type as “title”, the content may be different for each business operator or service.

  Note that “title” corresponds to the title of the content, “url” corresponds to a URL (Uniform Resource Locator) for acquiring the content, “date” corresponds to the broadcast date of the content, and “id” corresponds to the content. “Distributor” corresponds to an identifier for identifying a provider that provides content. These metadata are merely examples, and metadata other than these may exist. For example, it may be the length of the content playback time.

  If “id” is included as metadata in all contents, the same contents can be identified using this “id”. However, there are various providers that provide each content, and “id” is not necessarily included. Even if “id” is included, if “id” is assigned based on a different standard for each business operator, the same content cannot be identified using this “id”.

  Therefore, in each embodiment, not only using one type of metadata but also using a plurality of types of metadata increases the accuracy of identifying the same content.

  FIG. 6B shows an example of the metadata after shaping stored in the metadata management DB 12. This is obtained by the metadata shaping unit 11 shaping and classifying the metadata shown in FIG.

  For example, metadata corresponding to “summary” of each content is registered in the “summary” table in FIG. Also, “5th ** Story October 18 Broadcast” is formatted as “title” for “5th ** Story” and “20161018” for “18th October Broadcast”. “Registered in the table.

  FIG. 6C shows an example of the metadata similarity stored in the metadata similarity management DB 22. This is because each of the n metadata similarity management DBs 22 compares the metadata with reference to the shaped metadata shown in FIG. 6B, calculates the metadata similarity, and calculates the metadata. It is stored in the similarity management DB 22.

For example, referring to the metadata similarity S ₂ that is the metadata similarity of “title”, the metadata similarity of “** story (5)” and “continuous television drama ** story (5)” is “0. The metadata similarity between “** Story (5)” and “Noon News October 18 broadcast” is a low value of “0.1”.

FIG. 6-4 shows an example of content identity stored in the content identity management DB 32. This is because each of the m content identity calculation units 31 calculates the content identity for all combinations of content with reference to the metadata similarity shown in FIG. 6-3 and stores it in the content identity management DB 32. Is.
For example, the content identity calculation unit 31-1 calculates the content identity I _{1 according} to the following [Equation 1].

[Formula 1]
I ₁ = S ₁ + 1.5S ₂ + 0.5S ₃ + 0.3S ₄

This indicates that a value obtained by adding a weighting value to each of the metadata similarities S _{1 to} S ₄ calculated for each type of metadata is calculated as the content identity. Incidentally, other content identical calculation unit 31, such as contents same calculator 31-2 and content identical calculation unit 31-3, a content identical degree given different weighting value to the metadata similarity S ₁ to S ₄ Is calculated.

Each database is constructed as described with reference to FIGS.
Next, the creation of the content acquisition method list thereafter will be described.
The user passes information for uniquely specifying the desired content to the content acquisition method list creation unit 41. First, the content acquisition method list creation unit 41 refers to the metadata similarity management DB 22 to resolve specific content from the passed content information. For example, if the user inputs “** Story (5)” and “October 18 broadcast” as information for uniquely specifying the content, the “content acquisition method list creation function” is the metadata management DB. For example, title "is resolved to the content of" ** Story (5) ".

  Next, the content acquisition method list creation unit 41 creates a viewing method list for the content with reference to the content identity management DB 32 and passes it to the user.

For example, it is assumed that the content acquisition method list creation unit 41 refers to the content identity I ₁ calculated by the content identity calculation unit 31-1. In this case, the content desired by the user is “title” (“Story (5)”, “Continuous TV novel ** story (5)”) and “5th ** story” in descending order of content identity. “October 18 broadcast”, and as a list of ranking and acquisition methods, URLs for acquiring these contents are “arib: // lll”, “http: // mmm”, “Http: // oooo” is returned.

The content acquisition method list creation unit 41, and with reference to the content same degree I ₂ calculated content identical calculation unit 31-2. In this case, the contents desired by the user are “title” (“Story (5)”), “Continuous TV novel ** story (5)”, “5th ** story” in order from the highest content identity. “October 18th broadcast”, “5 minutes ** story”, “noon news October 18th broadcast”, and acquire these contents as a list of ranking and acquisition methods URLs “arib: /// llll”, “http: // mmm”, “http: // ooo”, “http: // nnn”, “http: // ppp” are returned.

  The user can enjoy the content by selecting an acquisition method suitable for the user's situation and device function from the content acquisition method list that has been passed.

  The three embodiments and examples thereof have been described above. Each of the above-described embodiments is a preferred embodiment of the present invention. However, the scope of the present invention is not limited to only the above-described embodiments, and various modifications can be made without departing from the spirit of the present invention. Implementation in a modified form is possible. For example, it is possible to make changes as described below.

  In each of the above-described embodiments, the media to be delivered and the delivery time are different, but the content having the same video and audio is the same content. In this regard, the concept of the same content may be expanded, and content that can be regarded as the same may be handled as the same content.

For example, the same content may be used even if the image quality differs. For example, content for so-called 4K broadcasting or 8K broadcasting and content for net distribution have different image quality even if they are the same content. Even in such a case, the content may be regarded as the same content. In addition, for example, a foreign film or the like in which subtitles are inserted may be regarded as the same content as that in which no subtitles are inserted. Furthermore, for example, content that is dubbed in Japanese may be regarded as the same content.
However, if there is a difference in image quality or presence / absence of subtitles, it may not be regarded as the same content.

  In addition, for example, device types that can be used by the user may be registered in advance, and only content that can be acquired by the registered device may be included in the content acquisition method list.

  In addition, for example, one device in the embodiment may be realized by a combination of a plurality of computers. Alternatively, the plurality of devices in the embodiments may be realized by a single computer.

  In addition, in each of the above-described embodiments, a program distributed on a television or the like is handled as content, but each of the above-described embodiments may be realized for other content.

  Note that each of the devices included in each of the above embodiments can be realized by hardware, software, or a combination thereof. Further, the content identification method performed by the cooperation of the devices included in each of the above embodiments can also be realized by hardware, software, or a combination thereof. Here, “realized by software” means realized by a computer reading and executing a program.

  The program can be stored and provided to a computer using various types of non-transitory computer readable media. Non-transitory computer readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (for example, flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (for example, magneto-optical disks), CD-ROMs (Read Only Memory), CD- R, CD-R / W, and semiconductor memory (for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (random access memory)). The program may also be supplied to the computer by various types of transitory computer readable media. Examples of transitory computer readable media include electrical signals, optical signals, and electromagnetic waves. The temporary computer-readable medium can supply the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.

10 Metadata management means 11 Metadata shaping unit 12 Metadata management DB
20 Metadata Similarity Management Unit 21 Metadata Similarity Calculation Unit 22 Metadata Similarity Management DB
30 Content identity management means 31 Content identity calculation unit 32 Content identity management DB
40 Content acquisition method list creation unit 41 Content acquisition method list creation unit 50 Similarity / identity management unit 51 Similarity / identity calculation unit 52 Content identity management DB
60 Content combination management DB
70 Calculation Result Reduction Units 101, 102, 103 Content Identification Device

Claims (6)

For each of a plurality of contents, metadata that is data indicating the characteristics of the contents attached to the contents is acquired based on a predetermined metadata acquisition method, and the acquired metadata is classified for each type of metadata. Metadata management means to be stored;
Similarity calculation means for calculating the similarity between the metadata for each type of the metadata accumulated by the metadata management means;
On the basis of the similarity calculated by the similarity calculation means, the degree of similarity calculation means for calculating the degree of identity between the content and other content other than the content;
And a list creation unit that creates a list of metadata including a content acquisition method that is specified as the same content as the specified content, based on the degree of identity between the content calculated by the identity level calculation unit. Content identification device. The content identification device according to claim 1,
The list creation means includes:
When a list request including content specification is received from a user, the content specified as the same content as the content specified by the list request is based on the degree of identity between the content calculated by the identity level calculation means. A content identification device that creates a metadata list including an acquisition method and outputs the created list to the user as a response to the list request. The content identification device according to claim 1 or 2,
The degree-of-identity calculation means gives different weights to the similarities between the metadata calculated by the similarity calculation means, depending on the type of the metadata,
The degree-of-identity calculation unit is a content identification device that calculates the degree of identity between contents based on a value obtained by adding the similarities of the weighted metadata in units of contents. The content identification device according to any one of claims 1 to 3,
The degree-of-identity calculation means includes a plurality of degree-of-identity calculation units for calculating the degree of identity between the contents.
The plurality of identity calculation units is a content identification device in which each of the plurality of identity calculation units calculates the degree of identity between the contents by different calculation methods. The content identification device according to any one of claims 1 to 4,
It further includes content combination management means,
The similarity calculation means calculates the similarity between the metadata for any of the types of metadata managed by the metadata management means, and the calculated similarity is equal to or greater than a predetermined reference. A combination of contents corresponding to each metadata is stored in the content combination management means,
For the combination of contents not stored in the content combination management means, the calculation of the similarity between the metadata by the similarity calculation means, the calculation of the degree of identity between the contents by the identity calculation means, Content identification device that does not perform   A program for causing a computer to function as the content identification device according to any one of claims 1 to 5.

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