Title :
The MovieOracle - Content Based Movie Recommendations
Author :
Nessel, Jochen ; Cimpa, Barbara
Author_Institution :
EdgeWorks Software Ltd. Ho Chi Minh City, Ho Chi Minh City, Vietnam
Abstract :
"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.
Keywords :
meta data; question answering (information retrieval); recommender systems; MovieOracle; Science Fiction; content based movie recommendation; human generated metadata; movie content; question answering; Books; Humans; Internet; Motion pictures; Prediction algorithms; Prototypes; Servers; content based prediction; inductive learning;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
Conference_Location :
Lyon
Print_ISBN :
978-1-4577-1373-6
Electronic_ISBN :
978-0-7695-4513-4
DOI :
10.1109/WI-IAT.2011.236
