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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-5392

Bouza, A; Reif, G; Bernstein, A; Gall, H (2008). SemTree: ontology-based decision tree algorithm for recommender systems. In: International Semantic Web Conference, Karlsruhe, Germany, 26 October 2008 - 30 October 2008.

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Abstract

Recommender systems play an important role in supporting people when choosing items from an overwhelming huge number of choices. So far, no recommender system makes use of domain knowledge. We are modeling user preferences with a machine learning approach to recommend people items by predicting the item ratings. Specifically, we propose SemTree, an ontology-based decision tree learner, that uses a reasoner and an ontology to semantically generalize item features to improve the effectiveness of the decision tree built. We show that SemTree outperforms comparable approaches in recommending more accurate recommendations considering domain knowledge.

Item Type:Conference or Workshop Item (Other), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
DDC:000 Computer science, knowledge & systems
Uncontrolled Keywords:Recommender System, Ontology-Based Decision Tree, User Model, Feature Creation, Semantic Web, Ontology
Language:English
Event End Date:30 October 2008
Deposited On:21 Nov 2008 09:53
Last Modified:09 Jul 2012 03:24
Official URL:http://iswc2008.semanticweb.org/
Related URLs:http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-401/iswc2008pd_submission_87.pdf
http://seal.ifi.uzh.ch/bouza (Author)
http://www.ifi.uzh.ch/ddis/people/amancio-bouza (Author)
Citations:Google Scholar™

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