A Review on Improving the Clustering Performance in Text Mining

Authors

  • Ashwini Harishchandra Ghonge  M. Tech, Computer Science Engineering, Guru Nanak Institute of Engineering and Technology, Nagpur, Maharashtra, India
  • Prof. Vijaya Kamble  Computer Science Engineering, Guru Nanak Institute of Engineering and Technology, Nagpur, Maharashtra, India

Keywords:

Clustering Techniques, Co-Clustering,Constrained Clustering, Semi-supervised Learning, Text Mining.

Abstract

Lately, the improvement of data frameworks in each field, for example, business, scholastics, and the drug have prompted increment in the measure of put away information step by step. A lion's share of information is put away in archives that are practically unstructured. Content mining innovation is exceptionally useful for individuals to process immense data by forcing structure upon content. Clustering is a well-known procedure for automatically sorting out a huge gathering of content. Nonetheless, in genuine application spaces, the experimenter has some foundation learning that helps in clustering the information. Customary clustering strategies are somewhat unsatisfactory of various information types and can't deal with sparsity and high dimensional information. Co-clustering strategies are received to defeat the customary clustering strategy by at the same time performing report and word clustering taking care of the two insufficiencies. Semantic comprehension has turned out to be a fundamental element for data extraction, which is made by receiving requirements as a semi-supervised learning technique. This overview audits on the compelled co-clustering techniques embraced by specialists to support the clustering execution.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2019-02-28

Issue

Volume 6, Issue 1, January-February-2019

Section

Research Articles

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How to Cite

[1]
Ashwini Harishchandra Ghonge, Prof. Vijaya Kamble, " A Review on Improving the Clustering Performance in Text Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 1, pp.380-385, January-February-2019.