Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2009

Abstract

Web video categorization is a fundamental task for web video search. In this paper, we explore the Google challenge from a new perspective by combing contextual and social information under the scenario of social web. The semantic meaning of text (title and tags), video relevance from related videos, and user interest induced from user videos, are integrated to robustly determine the video category. Experiments on YouTube videos demonstrate the effectiveness of the proposed solution. The performance reaches 60% improvement compared to the traditional text based classifiers.

Keywords

Categorization, Classification, Context, Social web, Web video

Discipline

Data Storage Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 17th ACM international conference on Multimedia, MM'09, Beijing, China, October 19-24

First Page

1109

Last Page

1110

ISBN

9781605586083

Identifier

10.1145/1631272.1631522

Publisher

ACM

City or Country

Beijing, China

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