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Title:
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A SEMANTIC-BASED RECOMMENDER SYSTEM FOR THE SBTVD |
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Author(s):
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Glauco da Silva, Laércio Augusto Baldochi Júnior |
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ISBN:
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978-972-8939-30-4 |
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Editors:
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Hans Weghorn, Pedro Isaías and Radu Vasiu |
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Year:
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2010 |
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Edition:
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Single |
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Keywords:
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Recommender systems, ontologies, spreading activation, interactive digital television |
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Type:
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Full Paper |
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First Page:
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111 |
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Last Page:
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118 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper presents an hybrid recommender system which exploits well succeeded strategies for recommending TV shows. Using reasoning techniques, we developed a content-based recommender that is able to discover knowledge about the users preferences. We use this knowledge to build a profile that can be used (a) to recommend shows available in the TV schedule and (b) as an input to an external collaborative filtering recommender. When both recommenders work together, the provided results are significantly more effective, reducing overspecialization and producing unexpected but relevant recommendations. |
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