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2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology
The MovieOracle - Content Based Movie Recommendations
Lyon, France
August 22-August 27
ISBN: 978-0-7695-4513-4
"What movies do you like?" Everyone has had to answer this question at least once. And the answer is often given by means of examples: "I like Star Wars." Often an examples explains a lot more than trying to characterize movies by other means, like giving a category like "Science Fiction" or providing actor or director names. The Movie Oracle recommends movies by comparing examples provided by the user to movie contents, which the Movie-Oracle derives from the movie dialogues gathered from movie subtitle files, without using any human generated meta-data.
Index Terms:
content based prediction, inductive learning
Citation:
Jochen Nessel, Barbara Cimpa, "The MovieOracle - Content Based Movie Recommendations," wi-iat, vol. 3, pp.361-364, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011
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