Hybrid Recommender Systems: Survey and Experiments Robin burke User Modeling and User-Adapted Interaction: Nov 2002; 12, 4; ABI/INFORM Global pg331 User Modeling and User-Adapted C 2002 Khuwer Academic Publi Hybrid Recommender Systems: Survey and Experiments ROBIN BURKE Department of Information Systems and Decision Sciences. California State University, Fuller CA 92834, USA Received 23 January 2000; accepted in revised form 24 September 2001) Abstract. Recommender systems represent user preferences for the purpose of suggesting items to purchase or examine. They have become fundamental applications in electronic commerce and information access, providing suggestions that effectively prune large information spaces so that users are directed toward those items that best meet their needs and preferences. a variety of techniques have been proposed for performing recommendation, inchuding content-base collaborative, knowledge-based and other techniques. To improve performance, these methods have sometimes been combined in hybrid recommenders. This paper surveys the landscape actual and possible hybrid recommenders, and introduces a novel hybrid, Entree C, a system that combines knowledge-based recommendation and collaborative filtering to recommend restaurants. Further, we show that semantic ratings obtained from the knowledge-based part Key words: case-based reasoning, collaborative filtering, electronic commerc 1. Introduction Recommender systems were originally defined as ones in which 'people provide rec- ommendations as inputs, which the system then aggregates and directs to appro- priate recipients'(Resnick Varian, 1997). The term now has a broade connotation, describing any system that produces individualized recommendations as output or has the effect of guiding the user in a personalized way to interesting or useful objects in a large space of possible options. Such systems have an obvious appeal in an environment where the amount of on-line information vastly outstrips any individual's capability to survey it. Recommender systems are now an integral part of some e-commerce sites such as Amazon. com and CDNow(Schafer, Konstan riedl, 1999) It is the criteria of 'individualized'and interesting and useful that separate the recommender system from information retrieval systems or search engines. The semantics of a search engine are 'matching the system is supposed to return all those items that match the query ranked by degree of match. Techniques such I The managing editor for this paper was Ingrid Zukerman Reproduced with permission of the copyright owner. Further reproduction prohibited without permissionReproduced with permission of the copyright owner. Further reproduction prohibited without permission. Hybrid Recommender Systems: Survey and Experiments Robin Burke User Modeling and User - Adapted Interaction; Nov 2002; 12, 4; ABI/INFORM Global pg. 331