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COLING
2010

Bipolar Person Name Identification of Topic Documents Using Principal Component Analysis

9 years 6 months ago
Bipolar Person Name Identification of Topic Documents Using Principal Component Analysis
In this paper, we propose an unsupervised approach for identifying bipolar person names in a set of topic documents. We employ principal component analysis (PCA) to discover bipolar word usage patterns of person names in the documents and show that the signs of the entries in the principal eigenvector of PCA partition the person names into bipolar groups spontaneously. Empirical evaluations demonstrate the efficacy of the proposed approach in identifying bipolar person names of topics.
Chien Chin Chen, Chen-Yuan Wu
Added 16 May 2011
Updated 16 May 2011
Type Journal
Year 2010
Where COLING
Authors Chien Chin Chen, Chen-Yuan Wu
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