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...
In automated multi-label text categorization, an automatic categorization system should output a category set, whose size is unknown a priori, for each document under analysis. Ma...
Claudine Badue, Felipe Pedroni, Alberto Ferreira d...
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...
In this paper we present a novel strategy, DragPushing, for improving the performance of text classifiers. The strategy is generic and takes advantage of training errors to succes...
Songbo Tan, Xueqi Cheng, Moustafa Ghanem, Bin Wang...
This paper studies noise reduction for computational efficiency improvements in a statistical learning method for text categorization, the Linear Least Squares Fit (LLSF) mapping...