A latent model for collaborative filtering

Helge Langseth, Thomas Dyhre Nielsen

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26 Citationer (Scopus)
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Resumé

Recommender systems based on collaborative filtering have received a great deal of interest over the last two decades. In particular, recently proposed methods based on dimensionality reduction techniques and using a symmetrical representation of users and items have shown promising results. Following this line of research, we propose a probabilistic collaborative filtering model that explicitly represents all items and users simultaneously in the model. Experimental results show that the proposed system obtains significantly better results than other collaborative filtering systems (evaluated on the MovieLens data set). Furthermore, the explicit representation of all users and items allows the model to, e.g., make group-based recommendations balancing the preferences of the individual users.
OriginalsprogEngelsk
TidsskriftInternational Journal of Approximate Reasoning
Vol/bind53
Udgave nummer4
Sider (fra-til)447–466
Antal sider20
ISSN0888-613X
DOI
StatusUdgivet - jun. 2012

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Collaborative filtering
Collaborative Filtering
Recommender systems
Recommender Systems
Dimensionality Reduction
Model
Balancing
Recommendations
Line
Experimental Results

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A latent model for collaborative filtering. / Langseth, Helge; Nielsen, Thomas Dyhre.

I: International Journal of Approximate Reasoning, Bind 53, Nr. 4, 06.2012, s. 447–466.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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