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Automatic and fast temporal segmentation for personalized news consuming

Author

Listed:
  • Yuan Dong

    (Beijing University of Posts and Telecommunications)

  • Shiguo Lian

    (France Telecom R&D (Orange Labs) Beijing)

Abstract

Automatic news program segmentation and classification becomes a hot topic, which reorganizes the news program according to the news’ topics, and provides the on-demand services to mobile consumers or Internet/home TV consumers. This paper presents a personalized news consuming system, including the system architecture, consumption steps and key techniques. Then, focused on the core technique, i.e., video temporal segmentation, the automatic video temporal segmentation method is proposed, evaluated and compared with existing ones. Experimental results show that the proposed scheme is computational efficient and gets higher correct detection rate. These properties make it a suitable choice for the personalized news consuming system.

Suggested Citation

  • Yuan Dong & Shiguo Lian, 2012. "Automatic and fast temporal segmentation for personalized news consuming," Information Systems Frontiers, Springer, vol. 14(3), pages 517-526, July.
    • Handle: RePEc:spr:infosf:v:14:y:2012:i:3:d:10.1007_s10796-010-9256-y
    DOI: 10.1007/s10796-010-9256-y
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    Cited by:

    1. Anastasia Griva & Cleopatra Bardaki & Katerina Pramatari & Georgios Doukidis, 2022. "Factors Affecting Customer Analytics: Evidence from Three Retail Cases," Information Systems Frontiers, Springer, vol. 24(2), pages 493-516, April.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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