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Feature weighting in content based recommendation system using social network analysis

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Feature weighting in content based recommendation system using social network analysis
We propose a hybridization of collaborative filtering and content based recommendation system. Attributes used for content based recommendations are assigned weights depending on their importance to users. The weight values are estimated from a set of linear regression equations obtained from a social network graph which captures human judgment about similarity of items. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval--information filtering General Terms Algorithms, Design, Experimentation Keywords Recommender System, Social Network, Feature Similarity
Souvik Debnath, Niloy Ganguly, Pabitra Mitra
Added 21 Nov 2009
Updated 21 Nov 2009
Type Conference
Year 2008
Where WWW
Authors Souvik Debnath, Niloy Ganguly, Pabitra Mitra
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