In many real-world recommendation tasks the available data consists only of simple interactions between users and items, such as clicks and views, called implicit feedback. In this kind of scenarios model based pairwise methods have shown of being one of the most promising approaches. In this paper, we propose a principled and efficient kernel- based collaborative filtering method for top-N item recommendation inspired by pairwise preference learning. We also propose a new boolean kernel, called Monotone Disjunctive Kernel, which is able to alleviate the sparsity issue that is one of the main problem in collaborative filtering contexts. The embedding of this kernel is composed by all the combina-Tions of a certain degree d of the input variables, and these combined features are semantically interpreted as disjunctions of the input variables. Experiments on several CF datasets have shown the effectiveness and the efficiency of the proposed kernel-based method.

Disjunctive Boolean Kernel based Collaborative Filtering for top-N item recommendation

Polato, Mirko
;
2017-01-01

Abstract

In many real-world recommendation tasks the available data consists only of simple interactions between users and items, such as clicks and views, called implicit feedback. In this kind of scenarios model based pairwise methods have shown of being one of the most promising approaches. In this paper, we propose a principled and efficient kernel- based collaborative filtering method for top-N item recommendation inspired by pairwise preference learning. We also propose a new boolean kernel, called Monotone Disjunctive Kernel, which is able to alleviate the sparsity issue that is one of the main problem in collaborative filtering contexts. The embedding of this kernel is composed by all the combina-Tions of a certain degree d of the input variables, and these combined features are semantically interpreted as disjunctions of the input variables. Experiments on several CF datasets have shown the effectiveness and the efficiency of the proposed kernel-based method.
2017
8th Italian Information Retrieval Workshop, IIR 2017
Lugano, Svizzera
2017
CEUR Workshop Proceedings
CEUR-WS
1911
97
100
http://ceur-ws.org/
Boolean kernels; Collaborative filtering; Implicit feedback; Kernel methods; Top-n recommendation; Computer Science (all)
Polato, Mirko; Aiolli, Fabio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1870214
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