Automatic detection of flash movie genre using bayesian approach

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

4 Scopus Citations
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Author(s)

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

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2004 IEEE International Conference on Multimedia and Expo (ICME)
Pages603-606
Volume1
Publication statusPublished - 2004

Publication series

Name
Volume1

Conference

Title2004 IEEE International Conference on Multimedia and Expo (ICME)
PlaceTaiwan
CityTaipei
Period27 - 30 June 2004

Abstract

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.

Research Area(s)

  • Bayesian classifier, Flash movie, Genre detection

Citation Format(s)

Automatic detection of flash movie genre using bayesian approach. / Ding, Dawei; Yang, Jun; Li, Qing et al.
2004 IEEE International Conference on Multimedia and Expo (ICME). Vol. 1 2004. p. 603-606.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review