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The study of text categorization has assumed special significance in the Internet era in helping us navigate the ocean of web pages and emails that continue to grow in an unrelenting pace. In many previous works on text classifications, it has been shown that composite features consisting of multiple word tokens like statistical phrases can contribute effectively to the classification task. However...
Automatic categorization of Web pages is an important area of study due to the rapidly growing amount of Web data. Efficient and accurate classification would greatly facilitate finding what one needs in the sea of information. Context-sensitive techniques have been proven to be effective in the classification task. However, the feature space for context feature that one can explore in these techniques...
One important problem facing text classifiers is the vast amount of features, many of which may not be relevant, that one can use in the classification process. Sleeping-Experts are one of those classifiers which can effectively deal with large number of irrelevant attributes. It is an online multiplicative weight updating algorithm similar to the Winnow algorithm. In its original design, it provided...
To evaluate the performance of text classifiers, we usually look at measures related to precision and recall, and most machine learning methods are optimized for these measures. In recent year, the use of receiver operating characteristics (ROC) graph and its extension area under the ROC curve (AUC) in gauging classifier performance has attracted much attention from the machine learning community...
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