Output details
11 - Computer Science and Informatics
University College London
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Output 0 of 0 in the submission
Output title
Matchbox: large scale online bayesian recommendations.
Type
E - Conference contribution
Name of conference/published proceedings
WWW
Volume number
-
Issue number
-
First page of article
111
ISSN of proceedings
-
Year of publication
2009
Number of additional authors
2
Additional information
<16> This paper presents Matchbox, a new probabilistic model and inference algorithm for recommender systems uniquely combining collaborative and content based recommendations. Instead of representing users and items as mere IDs, the model uses rich feature vectors to represent their meta-data. The rigorous formulation in terms of a fully probabilistic model makes it possible to mitigate the so-called cold-start problem and to track uncertainty associated with recommendations. The Matchbox algorithm is subject to US patent 12253854 and was the basis for the recently launched recommendation engine of Microsoft’s Xbox Live online gaming service with more than 40 million members.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
35
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
