In this paper, we propose the "Democratic Classifier", a simple, democracy-inspired patternbased classification algorithm that uses very short patterns for classificatio...
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
: This paper analyzes the influence of different parameters of Support Vector Machine (SVM) on text categorization performance. The research is carried out on different text collec...
Readers on the Web often skim through text to cope with the volume of available information. In a previous study [11] readers’ eye movements were tracked as they skimmed through...
Taxonomies of the Web typically have hundreds of thousands of categories and skewed category distribution over documents. It is not clear whether existing text classification tech...
Tie-Yan Liu, Yiming Yang, Hao Wan, Qian Zhou, Bin ...