This paper studies noise reduction for computational efficiency improvements in a statistical learning method for text categorization, the Linear Least Squares Fit (LLSF) mapping...
This paper describes a novel application of text categorization for mathematical word problems, namely Multiplicative Compare and Equal Group problems. The empirical results and a...
Suleyman Cetintas, Luo Si, Yan Ping Xin, Dake Zhan...
Abstract. Text Categorization algorithms have a large number of parameters that determine their behaviour, whose effect is not easily predicted objectively or intuitively and may v...
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...
Abstract. We present a possibly great improvement while performing semisupervised learning tasks from training data sets when only a small fraction of the data pairs is labeled. In...