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

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Souvik Debnath, Niloy Ganguly, Pabitra Mitra
• Keywords: Content Based Recommendation, Internet Technology, Keywords Recommender System, Social Network Graph, WWW 2008