International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Open Access | Double Blind Reviewed

ISSN: 2319-7064

Downloads: 124

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 1, January 2014

Evaluation of Similarities Measure in Document Clustering

Hemalatha Immandhi

Abstract: Clustering is a technique of collecting data into subsets in such a manner that identical instances are collected together, at the same time as different instances belong to different groups. The occurrences are thereby organized into an efficient depiction that characterizes the populace being sectioned. Clustering of entities is as earliest as the human need for describing the salient characteristics of mean and objects and identifying them with a style. Consequently, it squeezes a choice of scientific regulations from mathematics and statistics to biology and genetics, the entire of which uses different terms to describe the topologies formed using this analysis. As of biological taxonomies to medical syndromes and genetic genotypes to manufacturing group technology-the problem is same forming groups i. e. cluster text documents that have sparse and high dimensional data objects. Subsequently we originate new clustering criterion functions and corresponding clustering algorithms respectively. Divisive algorithms initiated with just only one cluster that contains all sample data. After that, the single cluster splits into two or more clusters that have higher dissimilarity between them until the number of clusters becomes number of samples or as specified by the user. The most important work is to build up a novel hierarchical algorithm for document clustering which provides maximum efficiency and performance. It is mainly spotlighted in studying and making use of cluster overlapping phenomenon to design cluster merging criteria. Recommending a new method to compute the overlap rate in order to improve time efficiency and the veracity is mainly concentrated. Multi-view learning algorithms characteristically assume a complete bipartite mapping between the different views in order to exchange information during the learning process. The remaining of this paper is ordered.

Keywords: Technology, clustering, Algorithm, data, analysis

Edition: Volume 3 Issue 1, January 2014,

Pages: 39 - 41

How to Download this Article?

You Need to Register Your Email Address Before You Can Download the Article PDF

How to Cite this Article?

Hemalatha Immandhi, "Evaluation of Similarities Measure in Document Clustering", International Journal of Science and Research (IJSR), Volume 3 Issue 1, January 2014, pp. 39-41,

Similar Articles with Keyword 'Technology'

Downloads: 184 | Weekly Hits: ⮙2 | Monthly Hits: ⮙3

Survey Paper, Computer Science & Engineering, India, Volume 7 Issue 1, January 2018

Pages: 81 - 84

Novel Approach to Virtual Machine Migration In Cloud Computing Environment - A Survey

Priyanka H [3] | Dr. Mary Cherian

Share this Article

Downloads: 0

Student Project, Computer Science & Engineering, India, Volume 11 Issue 1, January 2022

Pages: 455 - 459

Real World IoT Applications in Daily Domain

Eega Vivek Reddy | J Bala Krishna | Huzaifa Saad

Share this Article