ABSTRACT A breakneck progress of computers and web makes it easier to collect and store
large amount of information in the form of text; eg, reviews, forum postings, blogs, web …

Term clustering tries to group words based on the similarity criterion between words, so that
the groups can be used as the dimensions of the vector space in the text categorization. We …

Text mining is to research technologies to discover useful knowledge from enormous
collections of documents, and to develop a system to provide knowledge and to support in …

Text categorization is the technique used for sorting a set of documents into categories from
a predefined set. Text categorization is useful in better management and retrieval of the text …

Text data is the most common form of storing information. When engine search an query,
user obtained the large collection of text data. All this retrieve text data are not relevant to the …

This paper demonstrated the outcomes of the research of a number of general document
clustering and classification methods. Objectives: This research improves the clustering. Its …

Owing to the widely application in the fields of information retrieval, document analysis and
information extraction, document cluster analysis has been concerned broadly, and gotten a …

In this paper, we discuss a text categorization method based on k-means clustering feature
selection. K-means is classical algorithm for data clustering in text mining, but it is seldom …

The Document classification system is the field of data mining in which the format of data is
based on bag of words (BoW) or document vector model and the task is to build a machine …

High dimensionality of feature space and short of training documents are the crucial
obstacles for text categorization. In order to overcome these obstacles, this paper presents a …