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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings No
Title SemTree: ontology-based decision tree algorithm for recommender systems
Organization Unit
  • Amancio Bouza
  • G Reif
  • Abraham Bernstein
  • Harald Gall
Presentation Type other
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Event Title International Semantic Web Conference
Event Type conference
Event Location Karlsruhe, Germany
Event Start Date October 26 - 2008
Event End Date October 30 - 2008
Abstract Text 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.
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Keywords Recommender System, Ontology-Based Decision Tree, User , , Model, Feature Creation, Semantic Web, Ontology