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Text Mining, its Utilities, Challenges and Clustering Techniques

by Bhavna Bhardwaj
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 135 - Number 7
Year of Publication: 2016
Authors: Bhavna Bhardwaj
10.5120/ijca2016908452

Bhavna Bhardwaj . Text Mining, its Utilities, Challenges and Clustering Techniques. International Journal of Computer Applications. 135, 7 ( February 2016), 22-24. DOI=10.5120/ijca2016908452

@article{ 10.5120/ijca2016908452,
author = { Bhavna Bhardwaj },
title = { Text Mining, its Utilities, Challenges and Clustering Techniques },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 135 },
number = { 7 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 22-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume135/number7/24062-2016908452/ },
doi = { 10.5120/ijca2016908452 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:35:08.941306+05:30
%A Bhavna Bhardwaj
%T Text Mining, its Utilities, Challenges and Clustering Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 135
%N 7
%P 22-24
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text analysis is an interdisciplinary field of data mining in which person try to extract meaningful results from the unstructured textual data. In this paper the focus will be on different text mining application, the problems that we face while doing text mining and different text clustering approaches and try to figure out what next can be done for better performance of clustering algorithms.

References
  1. H. J. kamber and J. pei, Data Mining: Concepts and Techniques, San Francisco: Margan Kaufman, 2011.
  2. Text Classification Using Data Mining, S. M. Kamruzzaman1 Farhana Haider2 Ahmed Ryadh Hasan ICTM-2005.
  3. Web Data Mining, Chapter 9 Opinion Mining and Sentiment Analysis, Authors: Liu, Bing, Department of Computer Science, University of Illinois, Chicago, 851 S. Morgan St., Chicago, IL, 60607-7053, USA.
  4. Radev, D. R., Hovy, E., and McKeown, K. (2002). Introduction to the special issue on summarization. Computational Linguistics.
  5. A Survey on Automatic Text Summarization, Dipanjan Das Andre F.T. Martins, Language Technologies Institute Carnegie Mellon University{dipanjan, afm} @cs.cmu.edu,November 21, 2007IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 6, No 2, November 2012 ISSN (Online): 1694-0814 www.IJCSI.org.
  6. Techniques, Applications and Challenging Issue in Text Mining , Shaidah Jusoh and Hejab M. Alfawareh , College of Computer Science & Information Systems, Najran University P.O Box 1988, Najran, Saudi Arabia
  7. E.M. Voorhees. Implementing Agglomerative Hierarchical Clustering for use in Information Retrieval,Technical Report TR86–765, Cornell University, Ithaca, NY, July 1986.
  8. https://en.wikipedia.org/wiki/Complete-linkage_clustering
Index Terms

Computer Science
Information Sciences

Keywords

Text mining clustering Opinion mining

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