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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Association Rule Mining for Collaborative Recommender Systems

Lin, Weiyang 15 May 2000 (has links)
This thesis provides a novel approach to using data mining for e-commerce. The focus of our work is to apply association rule mining to collaborative recommender systems, which recommend articles to a user on the basis of other users' ratings for these articles as well as the similarities between this user's and other users' tastes. In this work, we propose a new algorithm for association rule mining specially tailored for use in collaborative recommendation. We make recommendations by exploring associations between users, associations between articles, and a combination of the two. We experimentally evaluated our approach on real data for many different parameter settings and compared its performance with that of other approaches under similar experimental conditions. Through our analysis and experiments, we have found that association rules are quite appropriate for collaborative recommendation domains and that they can achieve a performance that is comparable to current state of the art in recommender systems research.

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