Using contextual conditional preferences for recommendation taska: a case study in the movie domain

Aleksandra Karpus; Tommaso Di Noia; Paolo Tomeo; Krzysztof Goczyła

Using contextual conditional preferences for recommendation taska: a case study in the movie domain

Abstract

Recommendation engines aim to propose users items they are interested in by looking at the user interaction with a system. However, individual interests may be drastically influenced by the context in which decisions are taken. We present an attempt to model user interests via a set of contextual conditional preferences. We show that usage of proposed preferences gives reasonable values of the accuracy and the precision even when the dataset is quite small.

Authors (4)

Aleksandra Karpus dr inż.
Tommaso Di Noia prof. dott. ing.
- Politecnico di Bari Dipartimento di Ingegneria Elettrica e dell’Informazione
Paolo Tomeo MSc. Eng.
- Politecnico di Bari Dipartimento di Ingegneria Elettrica e dell’Informazione
Krzysztof Goczyła prof. dr hab. inż.

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Category:: Articles
Type:: artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Published in:: Studia Informatica Pomerania no. 37, pages 7 - 18,
ISSN: 2451-0424
Language:: English
Publication year:: 2016
Bibliographic description:: Karpus A., Di Noia T., Tomeo P., Goczyła K.: Using contextual conditional preferences for recommendation taska: a case study in the movie domain// Studia Informatica. -Vol. 37., nr. 1 (2016), s.7-18
Verified by:: Gdańsk University of Technology