Author-topic evolution analysis using three-way non-negative Paratucker

Authors:
Wei Peng;Tao Li
Affiliations:
Florida International University, Miami, FL, USA;Florida International University, Miami, FL, USA
Venue:
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2008

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Abstract

Analyzing three-way data has attracted a lot of attention recently due to the intrinsic rich structures in real-world datasets. The PARATUCKER model has been proposed to combine the axis capabilities of the Parafac model and the structural generality of the Tucker model. However, no algorithms have been developed for fitting the PARATUCKER model. In this paper, we propose TANPT algorithm to solve the PARATUCKER model. We apply the algorithm for temporal relation co-clustering on author-topic evolution. Experiments on DBLP datasets demonstrate its effectiveness.