@inproceedings{8ceb4854b50747f2a3dd2e7457523ef2,
title = "Automatic detection of flash movie genre using bayesian approach",
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.",
keywords = "Bayesian classifier, Flash movie, Genre detection",
author = "Dawei Ding and Jun Yang and Qing Li and Liping Wang and Liu Wenyin",
year = "2004",
month = dec,
day = "1",
language = "English",
isbn = "0780386035",
series = "2004 IEEE International Conference on Multimedia and Expo (ICME)",
pages = "603--606",
booktitle = "2004 IEEE International Conference on Multimedia and Expo (ICME)",
note = "2004 IEEE International Conference on Multimedia and Expo (ICME) ; Conference date: 27-06-2004 Through 30-06-2004",
}