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A TV News Recommendation System with Automatic Recomposition

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Advanced Multimedia Content Processing (AMCP 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1554))

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Abstract

In this paper, we propose a new recommendation system for a TV news with automatic recomposition. For the time consuming browsing of the TV news articles, we propose three modes of presentation, the digest mode, the relaxed mode, and the normal mode, where each presentation length is different. To make these presentation, TV news articles are decomposed, analyzed, and stored in the database scene by scene. Then, the system selects desired items and synthesizes these scenes into a presentation based on a user’s profile. For the profile of the user, we use a keyword vector and a category vector of news articles. The system is designed so that user’s control to the system becomes minimum. Therefore, a user only plays, skips, plays previous, and rewinds news articles in the system as same as an ordinary TV. However, different from an ordinary TV, the system collects user’s behavior while he uses the system. Based on this information, the system updates the user’s profile. We also show preliminary experimental results.

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References

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Author information

Authors and Affiliations

  1. Kobe University of Mercantile Marine, 5-1-1 Fukaeminami-cho, Higashinada-Ku, Kobe, Japan

    Junzo Kamahara

  2. FFC Limited, 1Fuji-machi, Hino-shi, Tokyo, Japan

    Yuji Nomura

  3. Department of Informatics and Mathematical Science, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka, Japan

    Kazunori Ueda & Hideo Miyahara

  4. Asahi Broadcasting Corporation, 2-48 2-chome, Oyodo-Minami, Kita-ku, Osaka, Japan

    Keishi Kandori

  5. Computer Center, Osaka University, 5-1Mihogaoka, Ibaraki, Osaka, Japan

    Shinji Shimojo

Authors
  1. Junzo Kamahara
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  2. Yuji Nomura
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  3. Kazunori Ueda
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  4. Keishi Kandori
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  5. Shinji Shimojo
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  6. Hideo Miyahara
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Editor information

Editors and Affiliations

  1. Graduate School of Engineering Department of Information Systems Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan

    Shojiro Nishio  & Fumio Kishino  & 

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© 1999 Springer-Verlag Berlin Heidelberg

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Kamahara, J., Nomura, Y., Ueda, K., Kandori, K., Shimojo, S., Miyahara, H. (1999). A TV News Recommendation System with Automatic Recomposition. In: Nishio, S., Kishino, F. (eds) Advanced Multimedia Content Processing. AMCP 1998. Lecture Notes in Computer Science, vol 1554. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48962-2_16

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  • DOI: https://doi.org/10.1007/3-540-48962-2_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65762-0

  • Online ISBN: 978-3-540-48962-7

  • eBook Packages: Springer Book Archive

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