Broadcast data utilization system and method

Abstract

By extracting valuable broadcast data from the broadcast data managed by broadcasting stations and providing it in a way that is of greater interest to viewers, we aim to promote the secondary use of broadcast data. [Solution] The broadcast data utilization system of the embodiment acquires broadcast data to be aired, automatically extracts and ranks attention data based on the number of occurrences from the broadcast data, analyzes and meta-analyzes the broadcast data based on the automatically extracted attention data to generate service-target broadcast information data that becomes useful information, generates ranking information from the service-target broadcast information data based on the ranking results, and adds the ranking information to the service-target broadcast information data and provides it to secondary users.

Description

Technical Field

[0001] This embodiment relates to a broadcast data utilization system and a method thereof.

Background Art

[0002] Broadcast data of programs and information broadcast from a broadcasting station includes highly reliable data with high value as primary information. However, the broadcasting station gives top priority to transmitting (broadcasting) broadcast data via broadcast waves. Therefore, in the broadcasting station, the burden of production and management required to extract valuable information data (hereinafter referred to as broadcast information data) from the broadcast data that has already been broadcast and is being managed as a broadcast target for secondary use is heavy.

[0003] On the other hand, as a distribution mechanism for promoting the secondary use of valuable broadcast information data, a broadcast data utilization system that accumulates and appropriately processes broadcast data has been developed and constructed. This system is based on a so-called broadcast data bank platform. Specifically, it uses AI (Artificial Intelligence) to analyze broadcast data, and through operations such as digest editing of videos included in the broadcast data, extraction of keywords, people, and objects, it meta-transforms individual broadcast data according to the purpose so as to be easy to use and generates broadcast information data. Regardless of the industry type, it is a mechanism that provides broadcast information data according to requests on a national scale. Also, it is possible to link with data such as SNS (Social Networking Service) and audience rating data as needed.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

[0005] As described above, conventional broadcast data utilization systems provide a distribution mechanism that extracts valuable broadcast information data from broadcast data aired by broadcasting stations and broadcast data managed as target broadcasts, and promotes secondary use. However, since they merely provide broadcast data as valuable information, there is a need to devise ways to provide broadcast information data that will be more interesting to viewers and to expand secondary use.

[0006] This embodiment has been made in view of the above-mentioned problems, and aims to provide a broadcast data utilization system and method that enables secondary use by extracting valuable broadcast data from broadcast data managed by broadcasting stations without burdening broadcasting stations, and providing it in a way that is of greater interest to viewers, and by developing a distribution mechanism for it, thereby contributing to the promotion of economic activity. [Means for solving the problem]

[0007] To solve the above problems, according to this embodiment, broadcast data to be aired is acquired, attention data based on the number of occurrences is automatically extracted from the broadcast data and ranked, the broadcast data is analyzed and meta-generated based on the automatically extracted attention data to generate service-target broadcast information data that will be useful information, ranking information is generated from the service-target broadcast information data based on the ranking results, and the ranking information is added to the service-target broadcast information data and provided to secondary users.

[0008] Specifically, the system accumulates broadcast data that has already aired or is scheduled to air, automatically extracts attention data from the broadcast data using at least one of speech recognition or video recognition, analyzes and meta-analyzes the broadcast data based on the automatically extracted attention data, automatically edits a digest of the broadcast data, obtains broadcast information data to be used as secondary information, and sets ranks for each piece of broadcast information data according to the content of each item (purpose of use, situation, etc.) requested by the secondary user. On the other hand, it extracts broadcast information data that matches the content of each item requested by the secondary user from the broadcast material data to be used as a service, and provides the extracted broadcast information data to the secondary user in a ranking format based on the rank set for each piece.

[0009] In other words, all broadcast data stored in the platform's cloud can be digitally handled, allowing it to be used with AI for operational purposes, segmented and provided to specific industries, and even ranked according to its level of attention.

[0010] Therefore, in this embodiment, when generating broadcast information data from accumulated broadcast data that can be secondarily used for retail, production management, etc., individual broadcast information data is ranked according to the purpose and circumstances of use, and can be provided in a ranking that suits the purpose of the user.

[0011] This allows for the instantaneous generation of trending broadcast information data based on accumulated broadcast data and its respective purposes and circumstances, and to provide it in a ranking format as elements that will be of greater interest to viewers, thereby contributing to the promotion of economic activity.

[0012] For example, it is conceivable to investigate trends (e.g., weekly trends) in broadcast information data such as video footage or POP (Point of Purchase advertising) for a particular product, rank individual broadcast information data, and utilize that ranking for production management. In this way, according to this embodiment, it is conceivable that the novel ranking approach could lead to the expansion of new revenue streams for broadcasting stations and the increased secondary use of unused broadcast data, thereby contributing to the revitalization of the broadcasting industry. [Brief explanation of the drawing]

[0013] [Figure 1] Figure 1 is a conceptual diagram showing an overview of the broadcast data utilization system according to the embodiment. [Figure 2] Figure 2 is a block diagram illustrating the schematic configuration of the collaborative model that embodies the broadcast data utilization system shown in Figure 1. [Figure 3] Figure 3 is a functional block diagram showing the schematic processing configuration of the broadcast data cloud platform, which is the core of the broadcast data utilization system shown in Figure 2. [Figure 4] Figure 4 is a flowchart showing the flow of database construction and analysis processing for collecting and analyzing broadcast data for the platform shown in Figure 3. [Figure 5] Figure 5 is a flowchart showing an example of processing by the broadcast data analysis / editing processing unit and the broadcast information data registration processing unit in the platform shown in Figure 2. [Figure 6] Figure 6 is a conceptual diagram illustrating the role of the platform in the broadcast data utilization system according to this embodiment. [Figure 7] Figure 7 is a flowchart showing the flow of broadcast information data generation and provision processing in the broadcast data utilization system according to the embodiment. [Figure 8] Figure 8 is a conceptual diagram showing an example of how broadcast information data is presented in a broadcast data utilization system according to the embodiment. [Modes for carrying out the invention]

[0014] The embodiments will be described below with reference to the drawings.

[0015] In recent years, Digital Transformation (DX) has been touted in various fields, and broadcasters are also beginning to utilize broadcast data (including source material) for secondary purposes, such as distributing it online after or simultaneously with broadcasting, or sharing information on social networking services (SNS). However, broadcasters face a heavy burden of personnel and equipment costs for producing and managing broadcast data for secondary use, such as online distribution, making efficient information dissemination difficult. At the same time, there is a demand to create value as highly reliable primary information from broadcast data that is aired, and to build a distribution system to promote the secondary use of this valuable information. Therefore, in this embodiment, a broadcast data utilization system is constructed that will contribute to the promotion of economic activity by extracting valuable broadcast data from broadcast data managed by broadcasters as airworthy content, enabling secondary use, and developing a distribution system, without burdening broadcasters.

[0016] Figure 1 is a conceptual diagram showing the configuration of a broadcast data utilization system according to an embodiment. In Figure 1, the broadcast data utilization system functions as a broadcast data bank built on a cloud server (not shown), and includes a broadcast data cloud platform (hereinafter referred to as the platform) 21 that collects broadcast data material from broadcasting stations 11, processes it in a format according to the request, and provides it. Note that the broadcasting station 11 for the platform 21 is not limited to one station, but can be handled individually even if there are multiple stations. It may also be a key station or a local station. Here, the number of times products A to D featured in the program are used (appeared) from the broadcast data material is counted, a rank is set for each product, and the usage ranking (ranking) of the products is determined based on their respective ranks. This ranking information for each product can be provided, for example, directly to retailers or through retail media. This makes it possible to use it, for example, for production management of product A, or for collaborative products in different industries.

[0017] Figure 2 is a functional block diagram showing the schematic configuration of a cooperation model that embodies the broadcast data utilization system shown in Figure 1. In Figure 2, the broadcasting station 11 distributes the broadcast data of programs to viewers such as consumers or operators through a broadcast tower T or a broadcast satellite S by means of a broadcast wave. For such a broadcast form, in this embodiment, a platform 21 that serves as the center of the broadcast data utilization system is provided. This platform 21 includes a communication interface (IF) 211 that receives broadcast data (materials) through a network 31 and transmits broadcast information data (product information, usage fees, etc.), and an information processing device 212 that extracts information corresponding to the usage purpose from the received broadcast data (materials) and performs editing processes such as ranking processing. Connected to the network 31 are, as participants in the cooperation model of this system, in addition to the broadcasting station 11, CM sponsors 41, banks / financial companies 42, product vendors 43, product manufacturers 44, advertising agencies 45, tourism operators 46, video content production / sales companies 47, various situation / environment surveyors (traffic situation / infrastructure situation, etc.) 48, EC (Electronic Commerce) / electronic settlement operators 49, etc., and data communication is possible among them.

[0018] Figure 3 is a functional block diagram showing the general processing configuration of the information processing device 212 of the broadcast data cloud platform 21, which is the core of the broadcast data utilization system shown in Figure 2. In the information processing device 212 shown in Figure 3, the broadcast data collection processing unit 2121 collects broadcast data (materials) for on-air provided by the broadcasting station 11 via the communication interface 211 and the network 31. The broadcast data analysis and editing processing unit 2122 analyzes the collected broadcast data (materials), extracts attention data where products, celebrities, etc. are presented using speech recognition and video recognition technology, and performs digest editing of the broadcast data according to the extracted attention data to generate service-oriented broadcast data that is useful information for viewers, performing so-called meta editing and editing according to the purpose of use. The broadcast information data registration processing unit 2123 processes the edited broadcast data into the requested format and registers the resulting broadcast information data in the database of the cloud server. The usage fee collection processing unit 2124 performs procedural processing for collecting usage fees when the broadcast information data is used by request, etc. The profit distribution processing unit 2125 distributes the profits from the collection of usage fees for broadcast information data to the broadcasting station 11.

[0019] FIG. 4 is a flowchart showing the flow of database construction and analysis processing in the broadcast data analysis / editing processing unit 2122 and the broadcast information data registration processing unit 2123 of the platform 12 shown in FIG. 3. In FIG. 4, the platform 21 sequentially accumulates the collected broadcast data (step S11) and performs database construction and analysis processing (step S12). In this process S12, videos such as products and landscapes are extracted and classified from the accumulated broadcast data (step S121), the number of appearances of the same or similar videos is counted (step S122), and ranking is performed based on the number of appearances of the same / similar videos (step S123). On the other hand, voices such as speech content, music by melody / instrument are separated from the accumulated broadcast data (step S124), the number of appearances of common or related voices is counted (step S125), and ranking is performed based on the number of appearances of common / related voices (step S126). Broadcast information data with the above video / voice ranking results added to the broadcast data is generated and registered to construct a database. This platform 12 waits for an analysis request (step S13). When there is an analysis request, it generates ranking information for the requested target and provides it to the requester (step S14), and ends a series of processes.

[0020] Figure 5 is a flowchart showing an example of processing by the broadcast data analysis and editing processing unit 2122 and the broadcast information data registration processing unit 2123 in the information processing device 212 of platform 21 shown in Figure 2. Specifically, the broadcast data analysis and editing processing unit 2122 waits for input of broadcast data to be aired provided by the broadcasting station 11 (step S21), and when broadcast data is input, it recognizes the audio and video contained in each broadcast data (step S22), extracts analysis targets such as keywords and celebrities from the recognition results (step S23), and generates broadcast information data by performing digest editing etc. on the analysis targets (step S24). Specifically, using speech recognition, AI (Artificial Intelligence) extracts keywords for products, etc., that are the focus of attention from the audio of the broadcast data (including the extraction of characteristic sound pressure changes in the audio (e.g., the emphasized part of "delicious")), the timecode of the relevant range containing the extracted keywords, and transcription. Using video recognition, AI extracts objects such as people (celebrities) that are the focus of attention from the video of the broadcast data, the timecode, and video features. From the audio and video recognition results, information to be analyzed is extracted, and the AI ​​edits the data by cutting out the beginning and end ±α to create a digest, etc., as data to improve the efficiency of broadcast operations. Subsequently, the broadcast information data registration processing unit 2123 registers the edited broadcast data as broadcast information data for service on the cloud server. If the extraction of analysis targets continues, the processes in steps S22 to S24 are repeated (step S25). When the extraction of analysis targets is completed, ranking is performed based on the number of occurrences of the analysis targets (step S26), the generated broadcast information data is registered in Betabase (step S27), and the series of processes ends. The broadcast information data registered in this manner will be used to build an ecosystem centered around broadcast data, aiming to expand opportunities for secondary use of broadcast data.

[0021] Specifically, the platform 21, with the above configuration, meta-formats broadcast data and consolidates it in one place as broadcast information data, building a new ecosystem with innovative presentation methods. It includes (1) a function to enable efficient information dissemination by broadcasting stations 11 as a secondary use analysis service for broadcast data, (2) a function to build a distribution system for broadcast data provision services as a secondary use provision service, and (3) a function to increase viewer attention.

[0022] (1) As a function for efficient information dissemination, as mentioned above, keywords and celebrities are extracted from broadcast data using speech recognition and video recognition technology, and metadata is automatically created by performing digest editing, etc., and the results of the analysis of the audio and video of the metadata-generated broadcast data are fed back to the broadcasting station. With this function, broadcasting stations can accelerate the secondary use of metadata data such as transcribed text information (subtitle insertion, etc.) in broadcast operations, such as rearranging the broadcast order, and furthermore, it is possible to obtain the feature quantities of the broadcast data material from the analysis results of the recognition process, and these material feature quantities can contribute to the efficiency of master operation. For example, master operation content can be compared and detected, and the application of the comparison results to subtitles can be considered.

[0023] (2) As a function to build a distribution mechanism for broadcast data provision services, the broadcast data meta-processed in (1) will be made public as a metadata database, and a business model will be built using Platform 21 that receives compensation in accordance with links from e-commerce sites and affiliates, thereby building a distribution mechanism for on-air broadcast data. The effect of this will be to provide a mechanism for secondary use of broadcast data, making it possible to revitalize the distribution of broadcast data and build a new ecosystem, and enabling the provision of reliable information closely related to daily life that is effective for viewers, consumers, businesses, etc.

[0024] (3) As a function to increase viewer attention, individual broadcast information data will be ranked according to the purpose and circumstances of use, and rankings will be provided according to the purpose of use. This function will enable broadcasters to expand new revenue streams and increase the secondary use of unused broadcast data through a new and innovative ranking system, thereby contributing to the revitalization of the broadcasting industry.

[0025] As described above, according to this embodiment, broadcast data that has already been aired and is scheduled to be aired is accumulated, attention data is automatically extracted from the broadcast data using at least one of speech recognition or video recognition processing, the broadcast data is automatically edited based on the automatically extracted attention data to obtain broadcast information data that will be used for secondary use services, and a rank is set for each piece of broadcast information data according to the content of each item (purpose of use, situation, etc.) requested by the secondary user. On the other hand, broadcast information data that matches the content of each item requested by the secondary user is extracted from the broadcast material data that will be used for the service, and the extracted broadcast information data that will be used for the service is provided to the secondary user in a ranking format based on the rank set for each. In other words, since all broadcast data accumulated in the platform's cloud can be digitally handled, it can be used for business operations using AI, or the data can be cut and provided to industries, and a rank corresponding to the level of attention can be set. Therefore, when generating broadcast information data that can be used for secondary use in retail, production management, etc. from the accumulated broadcast data, individual broadcast information data can be ranked according to the purpose of use and situation, and provided in a ranking that suits the purpose of the user. This enables the instantaneous generation of trending broadcast information data based on accumulated broadcast data and its respective uses and circumstances, and provides it in a ranking format as an element that will be of greater interest to viewers, thereby contributing to the promotion of economic activity. For example, it is conceivable to investigate trends (e.g., weekly trends) in broadcast information data such as video materials or POP (Point of Purchase advertising) for a certain product, rank individual broadcast information data, and utilize that ranking for production management. In this way, according to this embodiment, it is conceivable that the unprecedented new concept of ranking will lead to the expansion of new revenue for broadcasting stations and the expansion of secondary use of unused broadcast data, thereby contributing to the revitalization of the broadcasting industry.

[0026] The following describes the specific mechanism of the business model using the broadcast data utilization system according to this embodiment.

[0027] Broadcast data at a broadcasting station includes, for example, commercial data, program data (including subtitle data), on-screen text data, and broadcast progress data. Platform 21 takes broadcast data as input and uses AI-SaaS (Software as a Service) to extract attention data based on celebrities + keywords, such as keyword extraction from on-screen text (video recognition), keyword extraction from audio (speech recognition), and celebrity extraction from video (video recognition), and registers this data on a cloud server along with broadcast progress data and commercial / program data. Platform 21 analyzes and meta-generates the broadcast data based on the registered celebrity + keyword attention data, including broadcast progress data and commercial / program data. At this time, for example, AI-SaaS can identify the section in the broadcast data where a product (such as a local specialty) is searched based on a product keyword, edit that specific section into a digest, and then attach a 2D barcode (link data to the product provider) of the EC vendor (product provider) to the edited broadcast data, or add ranking information based on the ranking results of the frequency of occurrence, and provide it as broadcast information data. By doing this, when videos are posted on the websites of e-commerce vendors and affiliates, including barcodes or other link information and ranking information in the video allows for the expansion of business opportunities and direct purchases through broadcasting, which can then be used for effectiveness measurement.

[0028] Once broadcast data is meta-generated using the platform 21 described above, an ecosystem based on the meta-providing business can be established. For example, broadcast data can be effectively reused as a business model based on analysis results plus meta-providing, such as being used as meta for sales to e-commerce vendors and affiliates, or for analyzing lifestyle behavior predictions. Furthermore, by providing ranking information based on rankings when providing broadcast information data, it is possible to increase the utilization rate of the provided information.

[0029] As described above, Platform 21 provides Broadcast Station 11 with a multi-purpose cloud master (multi-purpose master for internet distribution, real-time AI subtitling, real-time operation monitoring, etc.) and a broadcast data utilization business. As a result, Broadcast Station 11 can reduce the costs of multi-purpose operations such as internet distribution, which are increasing, and move away from a model solely reliant on advertising revenue, by softwareizing its broadcast system, and generate new revenue other than advertising revenue through the utilization of broadcast data.

[0030] Meanwhile, in other industries, when a product or celebrity is featured on television, payment providers face challenges such as increased transaction volume, number of transactions, and number of participating merchants; retailers face sudden opportunity losses in inventory management; manufacturers need to optimize production and delivery; e-commerce businesses need to optimize inventory and product promotion; and video content providers face video editing costs, including the use of television footage. In response to this, Platform 21 makes it possible to utilize pre-broadcast data (pre-broadcast reports, AI-edited footage) that is not generally available to the public. For example, by providing broadcast data including information on products to be featured on television programs two weeks in advance, those who use broadcast data to promote their businesses can take proactive measures such as increasing production and delivery in advance to meet demand, securing product inventory and strengthening promotion, and reducing video editing costs.

[0031] Figure 6 is a conceptual diagram illustrating the role of platform 21 in the broadcast data utilization system shown in Figure 2. In Figure 6, by receiving ranking broadcast information data provided by platform 21, CM sponsors (manufacturers) 41 can determine whether the rank of the "product" featured in the program they sponsor is high or low. Banks and lending companies 42 can determine whether the rank of the "product" of their clients or borrowers is high or low, and whether their clients or borrowers are located in areas with high-ranking "scenery." Product vendors 43 can use the high rank of their products to plan sales events for advertising purposes. Product manufacturers 44 can decide on strategies to increase production volume if the rank of their manufactured products is high. Advertising agencies 45 can add emphasis to their advertising plans. Tourism operators 46 can use the data to help select tourist destinations and accommodations to promote and to plan pricing. Video content production and sales companies 47 can use the data as a reference to develop strategies for content production. The situation / environment survey company 48 can use the images for infrastructure inspection and traffic volume surveys because they are of good quality (high resolution) (they can also be used for accident investigation and crime investigation). The e-commerce / electronic payment company 49 can increase consumer purchasing intent by implementing measures such as increasing the number of points awarded when purchasing best-selling products.

[0032] Furthermore, affiliate marketers, local governments, and news websites could also be potential participants in this collaborative model. Additionally, further service expansion into other industries is conceivable, potentially extending to logistics, healthcare, education, human resources, entertainment, government agencies, and publishing professionals.

[0033] Figure 7 is a flowchart illustrating the flow of broadcast information data generation and provision processing for the broadcast data utilization system shown in Figure 2. In Figure 7, first, when a request for broadcast data utilization is entered by a user or operator (step S31), the system accepts input specifying whether the purpose of utilization is future or past (step S32). If the purpose of utilization is future, an analysis of the target market is performed (step S33), and based on the analysis results, buzzwords expected to become popular in the near future are generated by AI, and their ranking and ranking based on their frequency of occurrence are analyzed (step S34), and a proposal is created to create business opportunities that expand opportunities centered on the generated buzzwords (step S35). If the purpose of utilization is past, the system accepts input of search keys that match the purpose of utilization (step S36), analyzes the trend and ranking from the search results (step S37), and creates a proposal for product planning from the analysis results (step S38). The future-oriented proposal in step S35 and the past analysis proposal in step S38 are provided in the form of a so-called dashboard that allows the user to select information (step S39). When a user who has viewed the dashboard places an order for a requested proposal (step S40), the order data is provided to the designated recipient (step S41), and the series of processes is completed.

[0034] Here, the method for generating buzzwords using the broadcast data described above involves setting conditions that align with the purpose of use, such as period, location, and genre; performing AI analysis using learning data of trending patterns; extracting keywords from the AI ​​analysis results; counting the number of times they appear in the collected broadcast data; and outputting words with a count above a threshold as buzzword candidates. Ranking is based on the number of occurrences counted during buzzword generation.

[0035] As described above, proposals categorized by future and past can be offered to the following potential recipients. For example, in the case of sales utilization, proposals to promote products featured on television programs can be provided to retailers, restaurants, and advertising agencies; in the case of product development, proposals to understand trends from products used / featured on programs can be provided to manufacturers, SPA (Specialty store retailer of Private label Apparel), and restaurants; in the case of MD (merchandising), proposals to optimize inventory / production volume according to broadcast status can be provided to manufacturers, retailers, and restaurants; and in the case of research and analysis, proposals to visualize "events" from the past to the present can be provided to research companies, real estate companies, and local governments.

[0036] Figure 8 shows an example of a dashboard used in the model shown in Figure 7. In this example, the broadcast calendar displays the broadcast dates of product-related programs, and information on product-related programs on the specified date, their influence on purchasing behavior, etc., is displayed. For each program, information on the featured products is displayed, along with evaluation and ranking information. Here, when a dashboard viewer specifies a target period and requests the extraction of product-related programs, product-related programs within the specified period are extracted, and purchasing power is evaluated for each program, with ranking information added and displayed. Furthermore, recommended products and related products within the programs are extracted, and product information, comments, and reactions within the program are compiled and displayed in a list for each extracted product. If there is a request to purchase a product, the user is directed to the product purchase procedure screen. Although this example explains the case of product purchase, it can be implemented similarly when providing information on business partners, etc.

[0037] As described above, the broadcast data utilization system according to this embodiment not only utilizes future and past data of materials by meta-processing broadcast data, but also proposes a ranking method for the utilization process beyond meta-processing. As a new data proposal for broadcast data, it proposes creating several proposals from meta-processed materials using a buzzword generation AI, providing a data provision service through rankings, anticipating trends in advance, increasing supply, and thereby aiming to expand opportunities. Furthermore, as an application for MD (merchandising), it proposes utilizing broadcast information data to create business opportunities for expanding opportunities, providing data for the next product planning and seasonal proposals from broadcast information data, and providing ranking information to data recipients via a dashboard, thereby providing information to customers from various perspectives. In addition, meta-processing of materials is performed from the results of video and text recognition, and a trend AI that takes this meta-information and social trends as input performs buzzword generation, product planning generation, etc., and provides market analysis results tailored to the market in a ranking format.

[0038] As a result of the above proposal, purchase data will be provided to users, and the broadcasting station 11 will receive data usage fees along with the purchase data. This will make the usage fees, which are compensation for the provision of broadcast information data, a source of income for the broadcasting station 11, and will encourage the broadcasting station 11 to create new content. This will establish a series of collaborative models, allowing for the extraction of noteworthy data from the broadcast data managed by the broadcasting station 11 and enabling secondary use, without burdening the broadcasting station 11. It will also be possible to build a system that contributes to the promotion of economic activity by developing a distribution mechanism for the broadcast data provision service.

[0039] The platform 21 provides purchase data to system users and returns data usage fees to the broadcasting station 11 along with the purchase data. As a result, the usage fees, which are compensation for the broadcast data provision service, become a source of income for the broadcasting station 11, and the broadcasting station 11 becomes more motivated to create new content. This establishes a series of collaborative models, and without burdening the broadcasting station 11, it is possible to extract noteworthy data from the broadcast data managed by the broadcasting station 11 as on-air content, enable secondary use, and build a broadcast data utilization system that contributes to the promotion of economic activity by developing a distribution mechanism for the broadcast data provision service.

[0040] It should be noted that the present invention is not limited to the above embodiments, and the components can be modified and implemented in practice without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining the multiple components disclosed in the above embodiments. For example, some components may be deleted from all the components shown in the embodiments. Moreover, components from different embodiments may be appropriately combined. [Explanation of Symbols]

[0041] 10…Viewers (consumers, business owners, etc.), 11…Broadcasting stations, 21…Platforms, 211…Communication interfaces (IF), 212…Information processing equipment, 31…Networks, 41…CM sponsors, 42…Banks and lending companies, 43…Product vendors, 44…Product manufacturers, 45…Advertising agencies, 46…Tourism operators, 47…Video content production and sales companies, 48…Various situation and environmental survey companies (traffic conditions, infrastructure conditions, etc.), 49…EC and electronic payment companies.

Claims

1. A means of acquiring broadcast data to be aired, A means for automatically extracting and ranking attention data based on the frequency of appearance from the aforementioned broadcast data, and analyzing and meta-analyzing the broadcast data based on the automatically extracted attention data to generate service-target broadcast information data that becomes useful information, A means for generating ranking information from the broadcast information data subject to the service based on the ranking result, and for providing the broadcast information data subject to the service to a secondary user by adding the ranking information. A broadcast data utilization system equipped with the following features.

2. The aforementioned useful information is information obtained by automatically editing a digest of the aforementioned broadcast data. The broadcast data utilization system according to claim 1.

3. The aforementioned gaze data is obtained by accumulating the broadcast data and automatically extracting it from the accumulated broadcast data using at least one of the following processes: speech recognition or video recognition. The aforementioned ranking involves automatically editing the broadcast data based on the automatically extracted attention data and assigning ranks to the broadcast information data acquired for secondary use, according to the content of each item requested by the secondary user. The broadcast data utilization system according to claim 1.

4. The aforementioned ranking information is obtained by accumulating the aforementioned broadcast data, examining the trends in the accumulated broadcast information data, and ranking the individual broadcast information data. The broadcast data utilization system according to claim 1.

5. We obtain the broadcast data to be aired, From the aforementioned broadcast data, attention data based on the frequency of appearance is automatically extracted and ranked. Based on the automatically extracted gaze data, the broadcast data is analyzed and metadata is generated to produce useful service-targeted broadcast information data. Ranking information is generated from the broadcast information data subject to the service based on the ranking results. The aforementioned ranking information is added to the broadcast information data subject to the aforementioned service and provided to secondary users. How to utilize broadcast data.

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