Sciweavers

Share
CIKM
2008
Springer

Probabilistic polyadic factorization and its application to personalized recommendation

11 years 7 months ago
Probabilistic polyadic factorization and its application to personalized recommendation
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions of polyadic data in a principled way is a challenging research problem. Most existing methods separately analyze the marginal relationships among pairwise dimensions and then combine the results afterwards. Motivated by the fact that various dimensions of polyadic data jointly affect each other, we propose a probabilistic polyadic factorization approach to directly model all the dimensions simultaneously in a unified framework. We then show the connection between the probabilistic polyadic factorization and a non-negative version of the Tucker tensor factorization. We provide detailed theoretical analysis of the new modeling framework, discuss implementation techniques for our models, and propose several extensions to the basic framework. We then apply the proposed models to the application of personalized r...
Yun Chi, Shenghuo Zhu, Yihong Gong, Yi Zhang
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CIKM
Authors Yun Chi, Shenghuo Zhu, Yihong Gong, Yi Zhang
Comments (0)
books