Automatic and fast temporal segmentation for personalized news consuming

Yuan Dong () and Shiguo Lian ()
Additional contact information
Yuan Dong: Beijing University of Posts and Telecommunications
Shiguo Lian: France Telecom R&D (Orange Labs) Beijing

Information Systems Frontiers, 2012, vol. 14, issue 3, No 4, 517-526

Abstract: 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.

Keywords: Video temporal segmentation; Shot boundary detection (SBD); News segmentation; Personalized news consuming (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10796-010-9256-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:14:y:2012:i:3:d:10.1007_s10796-010-9256-y

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-010-9256-y

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().