Nomenclature and Contemporary Affirmation of the Unsupervised Learning in Text and Document Mining

Authors

  • Annaluri Sreenivasa Rao

  • Prof. S. Ramakrishna

Keywords:

Document clustering is primarily a method applied for an uncomplicated, document search, analysis and review of content or is a process of automatic c

Abstract

Document clustering is primarily a method applied for an uncomplicated, document search, analysis and review of content or is a process of automatic classification of documents of similar type categorized to relevant clusters, in a clustering hierarchy. In this paper a review of the related work in the field of document clustering from the simple techniques of word and phrase to the present complex techniques of statistical analysis, machine learning etc are illustrated with their implications for future research work.

How to Cite

Annaluri Sreenivasa Rao, & Prof. S. Ramakrishna. (2015). Nomenclature and Contemporary Affirmation of the Unsupervised Learning in Text and Document Mining. Global Journal of Computer Science and Technology, 15(C2), 15–21. Retrieved from https://computerresearch.org/index.php/computer/article/view/1142

Nomenclature and Contemporary Affirmation of the Unsupervised Learning in Text and Document Mining

Published

2015-01-15