Information theoretic approach for cold start users with diversity improvement technique for semantic recommender system. (2015)

• Record Type: Journal Article
• Authors: Kushwaha, Nidhi; Vyas, O.P.
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 10:Number 4(2015)
• Page Start: 281
• Page End: 290
• Publication Date: 2015
• Subjects: information theory -- intra list diversity -- global diversity -- popularity -- cold start users -- semantic recommender systems -- semantic web -- recommendation systems; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

This paper aims to use semantic database for recommendation purposes. It deals with two very specific problems of Recommendation System, namely Cold Start user and Diversity. We first describe cold start users and predict recommendation for them using information theory based methods. To introduce serendipitous results we also include aggregate diversity methods to the predicted ratings. Furthermore, we explain the results obtained from the rated items, and also increase the Intra List Diversity using a ranking-based approach that is different from the popularity-based approach employed in the past.