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
We address the e-rulemaking problem of categorizing public comments according to the issues that they address. In contrast to previous text categorization research in e-rulemaking...
Claire Cardie, Cynthia Farina, Adil Aijaz, Matt Ra...
This paper presents an approach to text categorization that i) uses no machine learning and ii) reacts on-the-fly to unknown words. These features are important for categorizing B...
Abstract. In this paper, we propose a probabilistic approach to feature selection for multi-class text categorization. Specifically, we regard document class and occurrence of eac...
Ke Wu, Bao-Liang Lu, Masao Uchiyama, Hitoshi Isaha...
When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...