Recent advances in computer and technology resulted into ever increasing set of
documents. The need is to classify the set of documents according to the type. Laying …

Purpose Text mining is growing in importance proportionate to the growth of unstructured
data and its applications are increasing day by day from knowledge management to social …

The purpose of this study is to develop a text clustering-based cause and effect analysis
methodology for incident data to unfold the root causes behind the incidents. A cause–effect …

Cloud storage is essential for managing user data to store and retrieve from the distributed
data centre. The storage service is distributed as pay a service for accessing the size to …

Social network analysis is a widely used technique to analyze relationships among wiki-
users in Wikipedia. In this paper the method to identify hidden social networks participating …

Recommender Systems (RS) have gradually progressed from the novelties used by few E-
business sites to an important component of business tools dealing the world of E …

Purpose Document management is growing in importance proportionate to the growth of
unstructured data, and its applications are increasing from process benchmarking to …

The authors propose clustering based multistep iterative algorithm. The important step is
where terms are grouped by synonyms. It takes advantage of semantic relativity measure …

This paper proposes architecture for the legal practitioners to lessen the burden of reading
full document. The iterative Latent Semantic Analysis (LSA)-based concept extracting and …

Similarity measurement is the important process in text processing. It measures the
similarities between the two documents. Unlabeled document collections are becoming …