Abstract
In this paper, we define reusable inference steps for content-based recommender systems based on semantically-enriched collections. We show an instantiation in the case of recommending artworks and concepts based on a museum domain ontology and a user profile consisting of rated artworks and rated concepts. The recommendation task is split into four inference steps: realization, classification by concepts, classification by instances, and retrieval. Our approach is evaluated on real user rating data. We compare the results with the standard content-based recommendation strategy in terms of accuracy and discuss the added values of providing serendipitous recommendations and supporting more complete explanations for recommended items. © 2010 Springer-Verlag.
Original language | English |
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Title of host publication | Proceedings of the 17th International Conference on Knowledge Engineering and Knowledge Management |
Editors | P. Cimiano, H.S. Pinto |
Place of Publication | Lisbon |
Pages | 431-440 |
DOIs | |
Publication status | Published - 2010 |
Event | 17th International Conference on Knowledge Engineering and Knowledge Management (EKAW2010) - Lisbon Duration: 1 Jan 2010 → 1 Jan 2010 |
Conference
Conference | 17th International Conference on Knowledge Engineering and Knowledge Management (EKAW2010) |
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Period | 1/01/10 → 1/01/10 |