Integrating Knowledge-based and Collaborative-filtering Recommender Systems

Abstract

Knowledge-based and collaborative-filtering recommender systems facilitate electronic commerce by helping users find appropriate products from large catalogs. This paper discusses the strengths and weaknesses of both techniques and introduces the possibility of a hybrid recommender system that combines the two approaches. An approach is suggested in which knowledge-based techniques are used to bootstrap the collaborative filtering engine while its data pool is small, and the collaborative filter is used as a postfilter for the knowledge-based recommender. Collaborative Filtering Collaborative filtering recommender system are a widelyaccepted technique in electronic commerce. (See [Resnick & Varian, 1997] and other articles in that special issue. A recent survey is found in [Maes, Guttman & Moukas, 1999]. See also [Goldberg et al. 1992] and [Resnick, et al. 1994].) These systems aggregate data about customers' purchasing habits or preferences and make recommendations to other...