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.
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Acknowledgment
The authors want to thank Dr. Christophe Garcia for sending COBALT platform’s temporal segmentation results for evaluation. This work was partially supported by the Invenio project launched by France Telecom.
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This work was partially supported by the Invenio project launched by France Telecom R&D (Orange Labs).
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Dong, Y., Lian, S. Automatic and fast temporal segmentation for personalized news consuming. Inf Syst Front 14, 517–526 (2012). https://doi.org/10.1007/s10796-010-9256-y
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DOI: https://doi.org/10.1007/s10796-010-9256-y