Including Item Characteristics in the Probabilistic Latent Semantic Analysis Model for Collaborative Filtering

Martijn Kagie (), M. van der Loos and M.C. van Wezel
Additional contact information
M.C. van Wezel: Erasmus Research Institute of Management (ERIM), RSM Erasmus University

No ERS-2008-053-MKT Revision_Date: 2009-07-29, Research Paper from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

Abstract: We propose a new hybrid recommender system that combines some advantages of collaborative and content-based recommender systems. While it uses ratings data of all users, as do collaborative recommender systems, it is also able to recommend new items and provide an explanation of its recommendations, as do content-based systems. Our approach is based on the idea that there are communities of users that find the same characteristics important to like or dislike a product. This model is an extension of the probabilistic latent semantic model for collaborative filtering with ideas based on clusterwise linear regression. On a movie data set, we show that the model is competitive to other recommenders and can be used to explain the recommendations to the users.

Keywords: algorithms; recommender systems; probabilistic latent semantic analysis; hybrid recommender systems (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp and nep-ecm
Date: 2008-08-27

Downloads: (external link)
http://hdl.handle.net/1765/13180 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:dgr:eureri:1765013180

Access Statistics for this paper

More papers in Research Paper from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
Series data maintained by ERIM Series Handler at the ERIM Office ().