Using contextual information in music playlist recommendations
Visualitza/Obre
10.3233/978-1-61499-806-8-166
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/132881
Tipus de documentCapítol de llibre
Data publicació2017
EditorIOSPress
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
Recommender Systems have become a fundamental part of various applications supporting users when searching for items they could be interested in,at a given moment. However, the majority of Recommender Systems generate isolate item recommendations based mainly on user-item interactions, without taking into account other important information about the recommendation moment, able to deliver users a more complete experience. In this paper, a hybrid Case-based Reasoning model generating recommendations of sets of music items, based on the underlying structures found in previous playlists, is proposed. Furthermore, the described system takes into account the similarity of the basic contextual information of the current and the past recommendation moments. The initial evaluation shows that the proposed approach may deliver recommendations of equal and higher accuracy than some of the widely used techniques.
CitacióGkatzioura, A.; Sànchez-Marrè, M. Using contextual information in music playlist recommendations. A: "Recent advances in artificial intelligence research and development. Proceedings of the 20th International Conference of the Catalan Association for Artificial Intelligence, Deltebre, Terres de l’Ebre, Spain, October 25–27, 2017". Amsterdam: IOSPress, 2017, p. 239-244.
ISBN978-1-61499-805-1
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Gatzioura&Sànchez-Marrè-CCIA17-revised.pdf | 186,1Kb | Visualitza/Obre |