Paper
29 January 2007 A study on video viewing behavior: application to movie trailer miner
Sylvain Mongy, Chabane Djeraba
Author Affiliations +
Proceedings Volume 6506, Multimedia Content Access: Algorithms and Systems; 65060N (2007) https://doi.org/10.1117/12.707593
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sylvain Mongy and Chabane Djeraba "A study on video viewing behavior: application to movie trailer miner", Proc. SPIE 6506, Multimedia Content Access: Algorithms and Systems, 65060N (29 January 2007); https://doi.org/10.1117/12.707593
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Video

Mining

Data modeling

Algorithm development

Error analysis

Expectation maximization algorithms

Multimedia

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