Holistic Entropy Reduction for Collaborative Filtering

Holistic Entropy Reduction for Collaborative Filtering

We propose a collaborative filtering (CF) method that uses behavioral data provided as propositions having the RDF-compliant form of (user X, likes, item Y ) triples. The method involves the application of a novel self-configuration technique for the generation of vector-space representations optimi...

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Bibliographic Details
Main Authors: Szwabe Andrzej, Misiorek Pawel, Janasiewicz Tadeusz, Walkowiak Przemyslaw
Format: Article
Language:English
Published: Sciendo 2014-07-01
Series:Foundations of Computing and Decision Sciences
Subjects:
collaborative filtering
self-configuration
propositional rdf-compliant data representation
quantum ir
information theory
Online Access:https://doi.org/10.2478/fcds-2014-0012

Internet

https://doi.org/10.2478/fcds-2014-0012

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