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Proceedings Paper

A study on video viewing behavior: application to movie trailer miner
Author(s): Sylvain Mongy; Chabane Djeraba
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Paper Abstract

In this paper, we present a study on video viewing behavior. Based on a well-suited Markovian model, we have developed a clustering algorithm called K-Models and inspired by the K-Means technique to cluster and analyze behaviors. These models are constructed using the different actions proposed to the user while he is viewing a video sequence (play, pause, forward, rewind, jump, stop). We have applied our algorithm with a movie trailer mining tool. This tool allows users to perform searches on basic attributes (cast, director, onscreen date...) and to watch selected trailers. With an appropriate server, we log every action to analyze behaviors. First results obtained from a set of beta users answering to a set of de.ned questions reveals interesting typical behaviors.

Paper Details

Date Published: 29 January 2007
PDF: 9 pages
Proc. SPIE 6506, Multimedia Content Access: Algorithms and Systems, 65060N (29 January 2007); doi: 10.1117/12.707593
Show Author Affiliations
Sylvain Mongy, LIFL, CNRS, Univ. of Lille 1 (France)
Chabane Djeraba, LIFL, CNRS, Univ. of Lille 1 (France)

Published in SPIE Proceedings Vol. 6506:
Multimedia Content Access: Algorithms and Systems
Alan Hanjalic; Raimondo Schettini; Nicu Sebe, Editor(s)

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