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.
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
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Additional Information | Date of conference: 30 June 2004 |
Item type | Book Section |
URI | https://vuir.vu.edu.au/id/eprint/10160 |
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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