Context-oriented web video tag recommendation

Zhineng Chen, Juan Cao, Yicheng Song, Junbo Guo, Yongdong Zhang, Jintao Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

Tag recommendation is a common way to enrich the textual annotation of multimedia contents. However, state-of-the-art recommendation methods are built upon the pair-wised tag relevance, which hardly capture the context of the web video, i.e., when who are doing what at where. In this paper we propose the context-oriented tag recommendation (CtextR) approach, which expands tags for web videos under the context-consistent constraint. Given a web video, CtextR first collects the multi-form WWW resources describing the same event with the video, which produce an informative and consistent context; and then, the tag recommendation is conducted based on the obtained context. Experiments on an 80,031 web video collection show CtextR recommends various relevant tags to web videos. Moreover, the enriched tags improve the performance of web video categorization.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th International Conference on World Wide Web, WWW '10
Pages1079-1080
Number of pages2
DOIs
StatePublished - Jul 20 2010
Event19th International World Wide Web Conference, WWW2010 - Raleigh, NC, United States
Duration: Apr 26 2010Apr 30 2010

Publication series

NameProceedings of the 19th International Conference on World Wide Web, WWW '10

Other

Other19th International World Wide Web Conference, WWW2010
CountryUnited States
CityRaleigh, NC
Period4/26/104/30/10

Keywords

  • context-oriented
  • social tagging
  • tag recommendation
  • web video

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