Towards google challenge: combining contextual and social information for web video categorization

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.

REFERENCES

• 1: D. Brezeale, and D. J. Cook. Automatic Video Classification: A Survey of the Literature. IEEE Trans. on Systems, Man, and Cybernetics, vol. 38, no. 3, May 2008, pp. 416--430.
• 2: L. Yang, J. Liu, X. Yang, and X.-S. Hua. Multi-Modality Web Video Categorization. MIR'07, pp. 265--274.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services
          Subjects: Web-based services

General Terms:
Algorithms, Design, Experimentation, Performance

Keywords:
categorization, classification, context, social web, web video