Automatic detection of flash movie genre using bayesian approach

Dawei Ding; Jun Yang; Qing Li; Liping Wang; Wenyin Liu

doi:10.1109/ICME.2004.1394264

Automatic detection of flash movie genre using bayesian approach

Dawei Ding
, Jun Yang
, Qing Li
, Liping Wang
, Wenyin Liu

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

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. © 2004 IEEE

Original language	English
Title of host publication	2004 IEEE International Conference on Multimedia and Expo (ICME)
Publisher	IEEE
Pages	603-606
Volume	1
ISBN (Print)	0780386035, 9780780386037
DOIs	https://doi.org/10.1109/ICME.2004.1394264
Publication status	Published - Jun 2004
Event	2004 IEEE International Conference on Multimedia and Expo (ICME 2004) - Taipei, Taiwan, China Duration: 27 Jun 2004 → 30 Jun 2004

Conference

Conference	2004 IEEE International Conference on Multimedia and Expo (ICME 2004)
Place	Taiwan, China
City	Taipei
Period	27/06/04 → 30/06/04

Research Keywords

Bayesian classifier
Flash movie
Genre detection

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10.1109/ICME.2004.1394264

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@inproceedings{43d1473716fd4989a278144818101115,

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. {\textcopyright} 2004 IEEE",

keywords = "Bayesian classifier, Flash movie, Genre detection",

author = "Dawei Ding and Jun Yang and Qing Li and Liping Wang and Wenyin Liu",

year = "2004",

month = jun,

doi = "10.1109/ICME.2004.1394264",

language = "English",

isbn = "0780386035",

volume = "1",

pages = "603--606",

booktitle = "2004 IEEE International Conference on Multimedia and Expo (ICME)",

publisher = "IEEE",

address = "United States",

note = "2004 IEEE International Conference on Multimedia and Expo (ICME 2004) ; Conference date: 27-06-2004 Through 30-06-2004",

}

TY - GEN

T1 - Automatic detection of flash movie genre using bayesian approach

AU - Ding, Dawei

AU - Yang, Jun

AU - Li, Qing

AU - Wang, Liping

AU - Liu, Wenyin

PY - 2004/6

Y1 - 2004/6

N2 - 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. © 2004 IEEE

AB - 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. © 2004 IEEE

KW - Bayesian classifier

KW - Flash movie

KW - Genre detection

UR - https://www.scopus.com/pages/publications/11244276993

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-11244276993&origin=recordpage

U2 - 10.1109/ICME.2004.1394264

DO - 10.1109/ICME.2004.1394264

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780386035

SN - 9780780386037

VL - 1

SP - 603

EP - 606

BT - 2004 IEEE International Conference on Multimedia and Expo (ICME)

PB - IEEE

T2 - 2004 IEEE International Conference on Multimedia and Expo (ICME 2004)

Y2 - 27 June 2004 through 30 June 2004

ER -

Automatic detection of flash movie genre using bayesian approach

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