SemTree: Ontology-Based Decision Tree Algorithm for Recomme...

SemTree: Ontology-Based Decision Tree Algorithm for Recommender Systems

inproceedings
Gerald Reif, Abraham Bernstein, Harald C. Gall, Amancio Bouza
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.
SemTree: Ontology-Based Decision Tree Algorithm for Recommender Systems
Poster
2008
Karlsruhe, Germany
In Proceedings of the 7th International Semantic Web Conference
October
ddis,s.e.a.l.