2011 | OriginalPaper | Chapter
A Model-Based EM Method for Topic Person Name Multi-polarization
Authors : Chien Chin Chen, Zhong-Yong Chen
Published in: Information Retrieval Technology
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In this paper, we propose an unsupervised approach for multi-polarization of topic person names. We employ a model-based EM method to polarize individuals into positively correlated groups. In addition, we present off-topic block elimination and weighted correlation coefficient techniques to eliminate the off-topic blocks and reduce the text sparseness problem respectively. Our experiment results demonstrate that the proposed method can identify multi-polar person groups of topics correctly.