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Exploiting synergy between ontologies and recommender systems

By Stuart E. Middleton, Harith Alani, Nigel R. Shadbolt and David C. De Roure

Abstract

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain.\ud This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Publisher: Sementic Web Workshop 2002, WWW2002
Year: 2002
OAI identifier: oai:oro.open.ac.uk:20058
Provided by: Open Research Online

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