Volume : V, Issue : IX, September - 2016
PERSONALIZING MOVIE RECOMMENDATION USING SEMANTIC CONTENTS IN COLLABORATIVE FILTERING
Kruti Jani, Dr. V. M. Chavda
Abstract :
Next generation recommender systems use Semantic Web technology and limit the problems of traditional approaches through inferences. In this paper, features extracted from Link open data cloud used to weight item-based collaborative filtering. This work deal with a large dataset, identify neighbors and predict the rating based on semantically weighted content. Evaluation using Open MovieLens datasets shows item based method and improved result than user-based collaborative-filtering
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DOI : https://www.doi.org/10.36106/gjra
Cite This Article:
Kruti Jani, Dr. V.M. Chavda PERSONALIZING MOVIE RECOMMENDATION USING SEMANTIC CONTENTS IN COLLABORATIVE FILTERING Global Journal For Research Analysis,Volume : 5 | Issue : 9 | September 2016
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Kruti Jani, Dr. V.M. Chavda PERSONALIZING MOVIE RECOMMENDATION USING SEMANTIC CONTENTS IN COLLABORATIVE FILTERING Global Journal For Research Analysis,Volume : 5 | Issue : 9 | September 2016