Exploiting Synergy Between Ontologies and Recommender Systems
Middleton, Stuart E., Alani, Harith, Shadbolt, Nigel R. and Roure, David C. De (2002) Exploiting Synergy Between Ontologies and Recommender Systems. In, Semantic Web Workshop 2002 At the Eleventh International World Wide Web Conference Hawaii, USA Sementic Web Workshop 2002, WWW2002.
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. 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.
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||Semantic Web Workshop 2002 At the Eleventh International World Wide Web Conference Hawaii, USA Organisation: ACM Address: Hawaii, USA|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Web & Internet Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > IT Innovation Centre
|Date Deposited:||15 Apr 2002|
|Last Modified:||27 Mar 2014 19:58|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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