Volume : 5, Issue : 9, September - 2016

PERSONALIZING MOVIE RECOMMENDATION USING SEMANTIC CONTENTS IN COLLABORATIVE FILTERING

Kruti Jani, Dr. V. M. Chavda

Abstract :

<p>&nbsp;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</p>