Abstract
Recently, people have begun searching for relevant information of each scene of TV program videos with other devices such as smartphones and tablets. While they view TV programs, users’ interests change by each scene of the video. When they try to get information related to the content of the scenes, users have to input appropriate query keywords for a Web search. However, it takes users time and effort to find their requested information. Although some data-casting services suggest related information to TV programs, the related information does not synchronize enough with each scene of the videos. To solve this problem, our system proposes a novel query keyword extraction method for Web searches, based on spatio-temporal features of videos using location names in the video caption data. We first extract all location names from the closed caption, and classify them into two types: main location name and sub-location names based on the occurrence frequency and average of the interval. Next, it determines subtopics from all nouns in TV program based on the same way as the classification of location names to generate web search queries. Therefore, suitable web pages for each scene can be found based on the generated query keywords through our system.
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Acknowledgements
This work was supported in part by JSPS KAKENHI Grant Number 16H01722 from the Ministry of Education, Culture, Sports, Science, and Technology of Japan.
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Kakimoto, H., Wang, Y., Kawai, Y., Sumiya, K. (2020). Query Generation for Web Search Based on Spatio-Temporal Features of TV Program. In: Ao, SI., Kim, H., Castillo, O., Chan, As., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9808-8_7
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DOI: https://doi.org/10.1007/978-981-32-9808-8_7
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