Automatic detection of Flash movie genre using Bayesian approach

Full text for this resource is not available from the Research Repository.

Ding, Dawei, Yang, Jun, Li, Qing, Wang, Liping and Wenyin, Liu (2004) Automatic detection of Flash movie genre using Bayesian approach. In: 2004 International Conference on Multimedia and Expo (ICME) : June 27-30, 2004, Taipei, Taiwan. IEEE, Piscataway, N. J., pp. 603-606.

Abstract

As Flash, a relatively new rich media format, becomes more and more popular on the Web, the 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 most likely to satisfy a user's information need. We present a method for detecting the Flash genre quickly and easily by employing a Bayesian approach. A feature set for representing genre information is proposed and used to build automatic genre classification algorithms. The performance of the proposed approach is 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

Dimensions Badge

Altmetric Badge

Additional Information

Date of conference: 30 June 2004

Item type Book Section
URI https://vuir.vu.edu.au/id/eprint/10160
DOI https://doi.org/10.1109/ICME.2004.1394264
ISBN 0780386035
Subjects Historical > FOR Classification > 0804 Data Format
Historical > FOR Classification > 1005 Communications Technologies
Historical > Faculty/School/Research Centre/Department > Australian Community Centre for Diabetes
Keywords ResPubID19457, genre detection, Bayesian classifier, Flash movie, real-world data set, Flash genre, classification, movie genre
Citations in Scopus 4 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login