An Ontology-based Contextual Pre-filtering Technique for Recommender Systems

Aleksandra Karpus; Iacopo Vagliano; Krzysztof Goczyła; Maurizio Morisio

doi:10.15439/978-83-60810-90-3

An Ontology-based Contextual Pre-filtering Technique for Recommender Systems

Abstrakt

Context-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort is required to change the method used. In this paper we present a new approach for contextual pre-filtering (i.e. using the current context to select a relevant subset of data). Our approach can be used with existing recommendation algorithms. It is based on two ontologies: Recommender System Context ontology, which represents the context, and Contextual Ontological User Profile ontology, which represents user preferences. We evaluated our approach through an offline study which showed that when used with well-known recommendation algorithms it can significantly improve the accuracy of prediction.

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Autorzy (4)

Aleksandra Karpus dr inż.
Iacopo Vagliano
- Politecnico di Torino Dept. of Control and Computer Engineering
Krzysztof Goczyła prof. dr hab. inż.
Maurizio Morisio prof.
- Politecnico di Torino Dept. of Control and Computer Engineering

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Informacje szczegółowe

Kategoria:: Aktywność konferencyjna
Typ:: materiały konferencyjne indeksowane w Web of Science
Tytuł wydania:: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems strony 411 - 420
ISSN:: 2300-5963
Język:: angielski
Rok wydania:: 2016
Opis bibliograficzny:: Karpus A., Vagliano I., Goczyła K., Morisio M..: An Ontology-based Contextual Pre-filtering Technique for Recommender Systems, W: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, 2016, Polish Information Processing Society,.
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.15439/978-83-60810-90-3
Weryfikacja:: Politechnika Gdańska