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Automatic detection of Flash movie genre using Bayesian approach

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.

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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

Item Type: Book Section
ISBN: 0780386035
Additional Information:

Date of conference: 30 June 2004

Uncontrolled Keywords: ResPubID19457, genre detection, Bayesian classifier, Flash movie, real-world data set, Flash genre, classification, movie genre
Subjects: Current > FOR Classification > 0804 Data Format
Current > FOR Classification > 1005 Communications Technologies
Historical > Faculty/School/Research Centre/Department > Australian Community Centre for Diabetes
Depositing User: VUIR
Date Deposited: 05 Jun 2013 03:58
Last Modified: 20 Mar 2019 22:35
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Citations in Scopus: 4 - View on Scopus

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