期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2012
卷号：2
期号：11
出版社：S.S. Mishra
摘要：Text categorizatio n has become one of the key techniques for handling and organizing text data. In practical text classification tasks, the ability to interpret the classification results is an important as the ability to classify exactly. This article will focus on the feature selection, for reducing the dimensionality of the vecto rs. We propose a new algorithm capable of partitioning a set of documents or other samples based on an embedding in a high-dimensional Euclidean space(i.e in which every document is a vector of real numbers, and then we apply classification techniques like knn for categorizations the data and finally evaluate the results by using precisions, etc.,
