Automatic detection of flash movie genre using bayesian approach

Dawei Ding, Jun Yang, Qing Li, Liping Wang, Liu Wenyin

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


As Flash - a relatively new rich media format becomes more and more popular on the Web, genre becomes increasingly important for Flash movie management as a complement to topical principles of classification. Genre classification can identify Flash movies authored in a style to most likely satisfy a user's information need. In this paper we present a method for detecting the Flash genre quickly and easily by employing a Bayesian approach. A feature set for representing genre information was proposed and used to build automatic genre classification algorithms. The performance of the proposed approach was evaluated by training a Bayesian classifier on real-world data sets. Classification results from our experiments on thousands of Flash movies demonstrate the usefulness of this approach.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Multimedia and Expo (ICME)
Number of pages4
Publication statusPublished - 1 Dec 2004
Externally publishedYes
Event2004 IEEE International Conference on Multimedia and Expo (ICME) - Taipei, Taiwan
Duration: 27 Jun 200430 Jun 2004

Publication series

Name2004 IEEE International Conference on Multimedia and Expo (ICME)


Conference2004 IEEE International Conference on Multimedia and Expo (ICME)


  • Bayesian classifier
  • Flash movie
  • Genre detection

ASJC Scopus subject areas

  • Engineering(all)

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