JP7196352B1 - Stream viewing analysis system, stream viewing analysis method and program - Google Patents

Abstract

An object of the present invention is to provide a stream viewing analysis system, a stream viewing analysis method, and a program that can be widely generalized beyond the certainty of viewer attributes or preferences. Kind Code: A1 A stream viewing analysis system includes an EC attribute assigning unit 43 for assigning an EC attribute to a viewer based on the viewer's Internet-related service ID based on the usage history of the Internet-related service, and the EC attribute assigning unit 43 assigns A viewing behavior analysis unit 44 that creates a population of viewers with common EC attributes and analyzes the viewing behavior of the population, and a recommendation unit 45 that makes recommendations based on the analysis results of the viewing behavior analysis unit 44. Prepare. [Selection drawing] Fig. 2

Description

The present invention relates to a stream viewing analysis system for analyzing viewing in broadcast stream transmission for transmitting streams via broadcasting.

Conventionally, as a viewing history analysis system of this type, as shown in Patent Document 1 below, in a broadcasting system, viewers of a television receiver generated using viewer data by transmitting a program to the television receiver A system is known for constructing a viewing estimation model that takes viewing history data as an input and outputs the likelihood that a viewer of a television receiver has a target viewer attribute or preference.

Japanese Patent Application Laid-Open No. 2021-027405

In such a broadcasting system, if a viewer's attribute or taste has a certain degree of certainty, it is possible to display content that matches that on the television receiver. , there was a problem that it is difficult to generalize this widely.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a stream viewing analysis system that can be used in a broadly generalized manner beyond the certainty of viewer attributes or preferences.

A stream viewing analysis system of a first invention is a stream viewing analysis system for analyzing viewer viewing in broadcast stream transmission for transmitting a stream via broadcasting,
an EC attribute assigning unit that assigns an EC attribute of the viewer based on the Internet-related service usage history based on the viewer's Internet-related service ID;
a viewing behavior analysis unit that creates a population of viewers having common EC attributes assigned by the EC attribute assignment unit and analyzes the viewing behavior of the population;
and a recommendation unit that makes a recommendation based on the analysis result of the viewing behavior analysis unit.

According to the stream viewing analysis system of the first invention, the EC attribute of the viewer is given from the Internet-related service usage history based on the viewer's Internet-related service ID, and the viewers with the common EC attribute By creating a population and analyzing viewing behavior for that population, this can be generalized beyond the dimension of likelihood of viewer attributes or preferences.

By making a recommendation based on the analysis result of the generalized viewing behavior, the result can actually be used for various recommendations.

As described above, according to the stream viewing analysis system of the first invention, it is possible to widely generalize and use the viewer's attributes or preferences beyond the certainty.

The stream viewing analysis system of the second invention is, in the first invention,
The viewing behavior analysis unit is characterized in that the analysis is performed using a heat map showing the viewing tendency of the viewer.

According to the stream viewing analysis system of the second invention, heat map analysis indicating viewing tendency (viewing frequency) can be performed as viewing behavior analysis. For example, if heat map analysis is performed on channels, days of the week, and time slots, it is possible to extract channels, days of the week, and time slots that people with the same EC attribute often watch.

In this way, according to the stream viewing analysis system of the second invention, it is possible to broadly generalize the certainty of the viewer's attribute or preference from multiple angles and actually use it for behavior analysis.

The stream viewing analysis system of the third invention, in the second invention,
The recommendation unit, based on the analysis result of the heat map by the viewing behavior analysis unit, recommends an area according to the viewing tendency as an advertisement delivery destination corresponding to the attributes of the population of the viewers. do.

According to the stream viewing analysis system of the third invention, as a result of the heat map analysis, it is possible to extract, for example, the channels, days of the week, and time slots that people with a specific EC attribute often watch. can be an advertisement placement destination according to the EC attribute of

In this way, according to the stream viewing analysis system of the third invention, it is possible to broadly generalize the certainty of the viewer's attributes or preferences from multiple perspectives, to actually use them for behavior analysis, and to Ad placement can be recommended to

The stream viewing analysis system of the fourth invention, in the second or third invention,
In stream transmission in which, in addition to the broadcast stream transmission, IP stream transmission for transmitting the stream via a network is performed,
The recommendation unit is characterized in that it recommends stream organization in the IP stream transmission based on the analysis result of the heat map by the viewing behavior analysis unit.

According to the stream viewing analysis system of the fourth invention, when IP stream transmission is performed in addition to broadcast stream transmission, a certain EC attribute is assigned based on the usage history of Internet-related services, and the attached EC attribute is Various recommendations for stream organization in IP stream transmission can be made from viewer behavior analysis in broadcasting of a common population.

In this way, according to the stream viewing analysis system of the fourth invention, the viewer's attribute or preference based on the broadcast stream is broadly generalized beyond the certainty, and is actually used for stream organization of IP stream transmission. can be done.

A stream viewing analysis method according to a fifth aspect of the present invention is a stream viewing analysis method for analyzing viewer viewing in broadcast stream transmission for transmitting a stream via broadcasting,
an EC attribute assigning step of assigning an EC attribute of the viewer based on the Internet-related service usage history based on the viewer's Internet-related service ID;
a viewing behavior analysis step of creating a population of viewers having common EC attributes imparted by the EC attribute imparting step and analyzing the viewing behavior of the population;
and a recommendation step of making a recommendation based on the analysis result of the viewing behavior analysis step.

According to the stream viewing analysis method of the fifth invention, the EC attribute of the viewer is given from the Internet-related service usage history based on the viewer's Internet-related service ID, and the viewers with the common EC attribute By creating a population and analyzing viewing behavior for that population, this can be generalized beyond the dimension of likelihood of viewer attributes or preferences.

By making a recommendation based on the analysis result of the generalized viewing behavior, the result can actually be used for various recommendations.

As described above, according to the stream viewing analysis method of the fifth invention, it is possible to widely generalize and use the viewer's attributes or preferences beyond the certainty.

A program of a sixth invention is a program for analyzing viewing by a viewer in broadcast stream transmission for transmitting a stream via broadcasting,
to the computer,
assigning EC attributes of the viewer from the Internet-related service usage history based on the viewer's Internet-related service ID;
Create a population of viewers who share the given EC attribute, analyze the viewing behavior of the population,
It is characterized by making a recommendation based on the analysis result of the viewing behavior.

According to the program of the sixth invention, the viewer's EC attribute is given from the Internet-related service usage history based on the viewer's Internet-related service ID, and a population of viewers who share the EC attribute is determined. By creating and analyzing viewing behavior for the population, this can be generalized beyond the dimension of likelihood of viewer attributes or preferences.

By making a recommendation based on the analysis result of the generalized viewing behavior, the result can actually be used for various recommendations.

As described above, according to the stream viewing analysis system of the sixth invention, it is possible to widely generalize and use the viewer's attribute or preference beyond the certainty.

1 is a system configuration diagram showing an overview of a stream viewing analysis system according to the present embodiment; FIG. FIG. 2 is a block diagram showing details of each processing unit in the stream viewing analysis system of FIG. 1;

As shown in FIG. 1, the stream viewing analysis system of the present embodiment includes, for example, broadcast stream transmission for transmitting a stream via broadcasting, network (unicast is preferable, but unicast and multicast may be used). ), a system for analyzing stream viewing in stream transmission in which IP stream transmission is performed to transmit the stream via a TV broadcast station 10 that transmits the broadcast stream, and an IP that transmits the IP stream. Broadcasting station 20, receiver 30 (corresponding to broadcast stream receiving means of the present invention) for receiving broadcast streams and IP streams, counting server 40, advertising space trading system 100 on the broadcasting side, and IP distribution side and an advertising space trading system 200 .

Note that the service platform including the IP broadcast station 20 is a platform that provides Internet-related services such as e-commerce, and is linked to the Internet-related service ID to record viewing history of IP stream transmission, which will be described later. In addition, the usage status of Internet-related services can be managed.

Details of each processing unit will be described below with reference to FIG.

A TV broadcasting station 10 that transmits a broadcast stream includes a sending unit 11 , an encoding unit 13 , a clock 16 and a clocking unit 17 .

The sending unit 11 performs transmission as so-called broadcasting. The transmission path is not limited to terrestrial broadcasting, but may be satellite broadcasting, cable television, IP retransmission or multicast as long as it is managed by the TV broadcasting station 10 . Further, the sending unit 11 performs processing such as multiplexing at the time of transmission.

The encoding unit 13 encodes information sources such as video, audio, and data. It should be noted that encryption is performed at the time of encoding, and key information required for decoding, which will be described later, is also generated and managed by the decoding unit. In this case, the key information is periodically transmitted from the transmission unit 11 .

The clock 16 is a so-called internal clock, and in this case serves as a reference clock that serves as a transmission reference time (broadcast time).

The clocking unit 17 gives the transmission reference time (broadcast time) of the clock 16 when transmitting encoded information sources such as video, audio, and data.

The IP broadcast station 20 that transmits IP streams includes a distribution unit 21 , an encoding unit 23 , a clock 26 and a clocking unit 27 .

The distribution unit 21 performs transmission as Internet distribution in addition to so-called IP network distribution.

The encoding unit 23 encodes information sources such as video, audio, and data for IP network distribution. It should be noted that encryption is performed at the time of encoding, and key information required for decoding, which will be described later, is also generated and managed by the decoding unit. In this case, the key information is periodically transmitted from the distribution unit 21 .

Clock 26 is a so-called internal clock.

The clocking unit 27 gives the time of the clock 26 to the information sources such as video, audio, and data when the information sources are distributed over the IP network.

The receiver 30 includes a receiver 31 , a buffer 32 , a decoder 33 , a reproducer 34 , a determiner 35 , a clock 36 , a recorder 37 and a communicator 38 .

The receiving unit 31 receives broadcast streams and IP streams as a communication interface. In addition to reception, the receiving unit 31 performs necessary processing such as demultiplexing when the transmitted broadcast stream data and IP stream data are multiplexed. Thereby, a channel (for example, 101ch, etc.) is acquired.

The buffer temporarily stores the broadcast stream data and IP stream data received by the receiver 31 . This enables stable decoding by the decoding unit 33, which will be described later, even if there is a temporary data loss.

The decoding unit 33 decodes the code of the information source such as video, audio, and data encoded by the encoding unit 13 of the TV broadcasting station 10, and decodes the information encoded by the encoding unit 23 of the IP broadcasting station 20. Performs processing to decode the code of information sources such as video, audio, and data. Note that the decoding unit 33 also executes necessary processing such as extraction of key information necessary for decoding when encryption is performed at the time of encoding.

The reproducing unit 34 reproduces the video/audio/data decoded by the decoding unit 33 .

The determination unit 35 has a function as a so-called audience rating measuring machine. That is, the stream reproduced by the reproducing unit 34 of the receiver 30 is identified and determined to generate a so-called viewing history (viewing log).

Note that the determination unit 35 may be configured outside the receiver 30 . For example, it may be a device for identifying and determining a stream reproduced by the reproducing unit 34 of the receiver 30, such as a so-called audience rating measuring device.

In addition to identifying the reproduced stream, the determination unit 35 may also have a function of identifying an individual who is watching. For example, the user near the receiver 30 is identified by short-range communication (communication with the user's smart phone using a beacon) to identify an individual or user ID. It may be configured to specify an individual or a user ID by input. The generation and accumulation of the viewing history can be performed by the user's selection using remote control input or the like.

Clock 36 is the internal clock of receiver 30 .

The recording unit 37 records various information. For example, the channel information acquired by the receiving unit 31 and the video/audio/data reproduced by the reproducing unit 34 are recorded with the time of the internal clock clocked by the clock 36, and decoded by the decoding unit 33. The transmission reference time and the viewing history, which is the result of determination by the determination unit 35, are stored.

The communication unit 38 is an interface for connection with an external server or the like via a network and has a security function. ing.

Aggregation server 40 includes aggregation unit 41 , accumulation unit 42 , EC attribute assignment unit 43 , viewing behavior analysis unit 44 , and recommendation unit 45 .

Aggregating unit 41 and accumulating unit 42 aggregate the viewing history (including receiver ID, user ID, household ID, and viewing time), which is the determination result of determining unit 35 of receiver 30, and store the aggregated information in accumulating unit 42. Accumulate viewing history.

The user ID is input to the receiver X by the user, and the household ID is issued for each household in the tabulation server and assigned to the receiver X. FIG.

The tallying unit 41 performs various analyzes of viewing conditions including the viewing rate. For example, the tabulation unit 41 tabulates exposure to programs and exposure to advertisements for each household, each user, and each receiver as an analysis of actual viewing conditions.

The EC attribute assigning unit 43 assigns the viewer's EC attribute based on the usage status of the Internet-related service linked to the Internet-related service ID.

It should be noted that the EC attribute assigning unit 43 does not necessarily have to be constructed within the aggregation server 40, and may be constructed in an external server such as a platform server for Internet-related services.

The viewing behavior analysis unit 44 creates a population of viewers who share the EC attributes assigned by the EC attribute assignment unit 43, and analyzes the viewing behavior of the population.

The recommendation unit 45 makes various recommendations based on the analysis result of the viewing behavior analysis unit 44 . The details of the content of the recommendation will be described later.

The advertising space trading system 100 on the broadcasting side and the advertising space trading system 200 on the IP distribution side are systems for trading advertisements such as CMs in broadcast streams and IP streams, respectively. In this embodiment, in particular, various recommendations may be made to advertisement purchasers and advertisement purchase applicants by the recommendation section via the advertising space trading system 100 on the broadcasting side and the advertising space trading system 200 on the IP distribution side.

It should be noted that security can be ensured in the various processes of the aggregation server 40 .

The above is the configuration of the stream viewing analysis system of the present embodiment. In the above configuration, each processing unit of the TV broadcasting station 10, the IP broadcasting station 20, the receiver 30, and the tallying server 40 is, for example, a CPU (Central Processing Unit), a ROM (Read Only memory), , RAM (random access memory) and other hardware, stores programs for executing various processes described later in a memory (not shown), and executes the programs to perform calculations for executing various processes It functions as a device (sequencer).

Part or all of the TV broadcasting station 10, the IP broadcasting station 20, the receiver 30, and the collection server 40 are configured by another server (external server), and a stream viewing analysis system is realized by distributed processing. may

Next, the details of the processing performed by the aggregation unit 41, the EC attribute assignment unit 43, the viewing behavior analysis unit 44, and the recommendation unit 45 will be described.

The counting unit 41 first acquires the viewing history of the TV broadcast and performs various analyzes of the actual viewing situation. For example, an analysis of viewing conditions such as the viewer's favorite program genre is performed. In addition to analysis of viewing history of broadcast streams, analysis of viewing history of IP streams can be performed.

The EC attribute assigning unit 43 assigns the viewer's EC attribute based on the usage status of the Internet-related service linked to the Internet-related service ID.

Here, the EC attributes include the use history of EC services (purchase history of goods and services), WEB behavior history, geographical movement history (walking, car, transportation), and IP stream viewing history. attributes can be given. Also, the EC attribute may be given by the following data fusion (data linkage).

For example, by data fusion (data linkage) of consumer data (consumer attribute information) obtained from various questionnaire surveys and user information linked to Internet-related service IDs (user usage history), the following Such attribute information (including EC attribute information) can be obtained.
<Persona image depiction line of sight>
・Overview of awareness of daily life ・Hobbies ・Leisure activities ・How to spend free time ・Frequently watched TV programs and video genres
・Product involvement
・Actual use of each media (television, digital, other) ・Information ・Purchase awareness <communication point of view>
・Reactions to advertisements and awareness characteristics ・Estimation of expected attitude changes in each media

Next, the viewing behavior analysis unit 44 creates a population having common EC attributes, and analyzes the population using a heat map showing viewing tendencies (viewing frequency). Specifically, the viewing behavior analysis unit 44 extracts, for example, channels, days of the week, and time slots that people with the same EC attribute often watch in broadcasts as high-frequency areas by heat map analysis.

Next, based on the analysis result of the heat map, the recommendation unit 45 selects an area (channel, day of the week, time period) with high viewing tendency (viewing frequency) as an advertisement delivery destination corresponding to the attribute of the population having the common EC attribute. to recommend.

Also, the recommendation unit 45 recommends a region (channel, day of the week, time zone) with a high viewing tendency (viewing frequency) as a stream organization (distribution organization) in IP stream transmission.

It should be noted that the recommendation unit 45 is not necessarily limited to a region (channel, day of the week, time zone) with a high viewing frequency as long as the region corresponds to the viewing tendency. You can also recommend areas (channels, days of the week, time slots) that have strong fans.

As a result, reliable EC attributes are assigned based on the usage history of Internet-related services, and stream organization recommendations for IP stream transmission can be made based on audience behavior analysis in broadcasts of a population having the assigned EC attributes in common. can.

As described in detail above, according to the stream viewing analysis system of the present embodiment, it is possible to widely generalize and use the viewer's attributes or preferences beyond the certainty.

In the present embodiment, a case has been described in which viewer behavior analysis is performed for broadcasts of a population having common EC attributes, but the present invention is not limited to this. Viewer behavior analysis may be performed using history.

When the viewer behavior analysis is performed based on the IP stream viewing history, it is possible to analyze the presence or absence of the IP stream usage history, usage trends, and frequency. In response to this, in Internet-related services, for example, distribution of channel and program advertisements (banners) that evoke and promote the use of IP stream services, as well as advertisements of high interest and interest, to applications, websites, and terminals. can do. Furthermore, it is possible to recommend an attribute corresponding to the usage tendency of the IP stream service and an area with a high viewing tendency (viewing frequency) to the advertising space trading system 200 on the IP distribution side.

As a result, viewer trend analysis can be performed by superimposing the IP stream viewing history on the broadcast stream viewing history. can be used for

In addition, in the present embodiment, a population having a common EC attribute is created for viewing trend analysis, but the present invention is not limited to this, and the creation of a population may be omitted as appropriate.

Furthermore, in this embodiment, VOD transmission may be used instead of IP transmission.

Further, in the present embodiment, the case where the receiver 30 is capable of receiving both the stream from the TV broadcast station 10 and the stream from the IP broadcast station 20 has been described. It doesn't have to be.

That is, the viewing history based on the receiver 30 capable of only receiving streams from the TV broadcasting station 10 may be processed by the aggregation server 40 (EC attribute assigning unit 43, viewing behavior analyzing unit 44). The viewing history based on the receiver 30 capable of only receiving streams from 20 may be processed by the collection server 40 (the EC attribute assigning unit 43 and the viewing behavior analysis unit 44).

DESCRIPTION OF SYMBOLS 10... TV broadcasting station 11... Sending part of TV broadcasting station 13... Encoding part of TV broadcasting station 16... Clock of TV broadcasting station 17... Stamping part of TV broadcasting station 20... IP broadcasting station 21... Distribution unit of IP broadcast station 23 Encoding unit of IP broadcast station 26 Clock of IP broadcast station 27 Timing unit of IP broadcast station 30 Receiver 31 Receiving unit 32 Buffer unit 33 Decoding unit 34 Reproducing unit 35 Judging unit 36 Clock 37 Recording unit 38 Communication unit 40 Aggregation server 41 Aggregation unit 42 Storage unit 43 EC attribute assignment unit 44... viewing behavior analysis unit, 45... recommendation unit, 100... advertising space trading system on the broadcasting side, 200... advertising space trading system on the IP distribution side.

Claims (6)

In a stream viewing analysis system that analyzes viewer viewing in broadcast stream transmission for transmitting streams via broadcasting,
an EC attribute assigning unit that assigns an EC attribute of the viewer based on the Internet-related service usage history based on the viewer's Internet-related service ID;
a viewing behavior analysis unit that creates a population of viewers having common EC attributes assigned by the EC attribute assignment unit and analyzes the viewing behavior of the population;
A stream viewing analysis system, comprising: a recommendation unit that makes a recommendation based on the analysis result of the viewing behavior analysis unit. The stream viewing analysis system according to claim 1,
The stream viewing analysis system, wherein the viewing behavior analysis unit performs analysis using a heat map showing viewing tendencies of the viewers. The stream viewing analysis system according to claim 2,
The recommendation unit, based on the analysis result of the heat map by the viewing behavior analysis unit, recommends an area according to the viewing tendency as an advertisement delivery destination corresponding to the attributes of the population of the viewers. stream viewing analysis system. 4. The stream viewing analysis system according to claim 2 or 3,
In stream transmission in which, in addition to the broadcast stream transmission, IP stream transmission for transmitting the stream via a network is performed,
The stream viewing analysis system, wherein the recommendation unit recommends stream organization in the IP stream transmission based on the analysis result of the heat map by the viewing behavior analysis unit. In a stream viewing analysis method for analyzing viewer viewing in broadcast stream transmission for transmitting a stream via broadcasting,
an EC attribute assigning step of assigning an EC attribute of the viewer based on the Internet-related service usage history based on the viewer's Internet-related service ID;
a viewing behavior analysis step of creating a population of viewers having common EC attributes imparted by the EC attribute imparting step and analyzing the viewing behavior of the population;
and a stream viewing analysis method, wherein a recommendation step of making a recommendation based on the analysis result of the viewing behavior analysis step is executed. A program for analyzing viewer viewing in broadcast stream transmission for transmitting a stream via broadcast,
to the computer,
assigning EC attributes of the viewer from the Internet-related service usage history based on the viewer's Internet-related service ID;
Create a population of viewers who share the given EC attribute, analyze the viewing behavior of the population,
A program comprising making a recommendation based on an analysis result of the viewing behavior.

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