The Use of Active Learning in Text Categorization
Ray Liere, Prasad V. Tadepalli · 1996
With the advent of large distributed and dynamic document collections (such as are on the World Wide Web), it is becoming increasingly importanto automate the task of text categ~zation. The use of machine learning in text categorization is difficult due to characteristics of the domain ~ including a very large number of input features, noise, and the problems associated with semantic analysis of text. As a result, the use of mpervised learning requires a relatively large number of labeled examples. W explore the possibility of using (almost) unsupervised learning and propose some novel approaches to using machine learning in this domain, 1.