This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
In this paper we propose a new approach to capture the inclination towards a certain election candidate from the contents of blogs and to explain why that inclination may be so. T...
In this paper, the task of text segmentation is approached from a topic modeling perspective. We investigate the use of latent Dirichlet allocation (LDA) topic model to segment a ...
In this paper we propose the multirelational topic model (MRTM) for multiple types of link modeling such as citation and coauthor links in document networks. In the citation networ...
Jia Zeng, William K. Cheung, Chun-hung Li, Jiming ...