Applying relevant set correlation clustering to multi-criteria recommender systems

Authors:
Nkechi J. Nnadi
Affiliations:
New Jersey Institute of Technology, Newark, NJ, USA
Venue:
Proceedings of the third ACM conference on Recommender systems
Year:
2009

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Abstract

This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N recommendations. With the advent of ecommerce sites that allow multi-criteria rating of items, there is an opportunity for recommender systems to use the additional information to gain a better understanding of user preference. This thesis proposes the use of the relevant set correlation model for a clustering-based collaborative filtering system. It is anticipated this novel system will handle large numbers of users and items without sacrificing the relevance of recommended items.