Automatic detection of Flash movie genre using Bayesian approach

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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.


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

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Additional Information

Date of conference: 30 June 2004

Item type Book Section
DOI 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
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