A Brief Survey On Text Mining, Its Techniques, And Applications

International Journal of Mobile Computing and Application
© 2021 by SSRG - IJMCA Journal
Volume 8 Issue 1
Year of Publication : 2021
Authors : Ms. Anushree Negi
pdf
How to Cite?

Ms. Anushree Negi, "A Brief Survey On Text Mining, Its Techniques, And Applications," SSRG International Journal of Mobile Computing and Application, vol. 8,  no. 1, pp. 1-6, 2021. Crossref, https://doi.org/10.14445/23939141/IJMCA-V8I1P101

Abstract:

A huge amount of information was caused by rapid development in computerized information collection strategies. About 80 percent of this information is constituted of unstructured or semi-organized information. A major problem is the recuperation of similar examples and trends for seeing material information from a vast amount of information. Text mining assumes a significant job of extricating helpful examples from unstructured content. Content mining is a method to discover important examples from the accessible content records. The example revelation from the content and report association of record is a notable issue in information mining. Text Mining has become a significant research zone. In this paper, the Survey of Text Mining procedures and applications have been introduced.

Keywords:

Text Mining, Information Extraction, Information Retrieval, Knowledge Discovery, Classification.

References:

[1] Mrs. SayantaniGhosh, Mr. Sudipta Roy, and Prof. Samir K. Bandyopadhyay. ―A tutorial review on Text Mining Algorithms‖, in International Journal of Advanced Research in Computer and Communication Engineering, 1(42012).
[2] Vishal Gupta, Gurpreet S. Lehal, ―A Survey of Text Mining Techniques and Applications‖ in Journal of Emerging Technologies in Web Intelligence, 1(1)(2009).
[3] Falguni N. Patel, Neha R. Soni., Text mining: A Brief Survey”, International Journal of Advanced Computer Research (ISSN (print): 2249-7277 ISSN (online): 2277-7970) 2(6)(2012).
[4] Jadhav, Amrut M., and Devendra P. Gadekar., A survey on text mining and its techniques., International Journal of Science and Research (IJSR) 3.11 (2014).
[5] N. Kanya and S. Geetha, “Information Extraction: A Text Mining Approach,” IET-UK International Conference on Information and Comm. Technology in Electrical Sciences,
[6] IEEE(2007), Dr. M.G.R. University, Chennai, Tamil Nadu, India,1111- 1118.
[7] S. M. Weiss, N. Indurkhya, T. Zhang, and F. Damerau, Text mining: predictive methods for analyzing unstructured information. (SpringerScience and Business Media, 2010.)
[8] Liritano S. and Ruffolo M., (2001), “ Managing the Knowledge Contained in Electronic Documents: a Clustering Method for Text Mining, IEEE, 454-458, Italy.
[9] Deepshikha Patel, Monika Bhatnagar, Mobile SMS Classification, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307 (Online), 1(1)(2011).
[10] Zhou Ning, Wu Jiaxin, Wang Bing and Zhang Shaolong (2008), “A Visualization Model for Information Resources Management,
12th International Conference Information Visualisation, China, IEEE, 57- 62.
[11] Rashmi Agrawal, Mridula Batra, A Detailed Study on Text Mining Techniques, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, 2(6)(2013).
[12] Henriksson, J. Zhao, H. Dalianis, and H. Bostr ̈om, ―Ensembles of randomized trees using diverse distributed representations of clinical events,‖ (BMC Medical Informatics and Decision Making, 16(2)(2016) 69.
[13] Y. Zhao, ―Analysing Twitter data with text mining and social network analysis,‖ in Proceedings of the 11th Australasian Data Mining and Analytics Conference (AusDM)(2013) 23.
[14] M. Cohen and W. R. Hersh, ―A survey of current work in biomedical text mining,‖ (Briefings in bioinformatics, 6(1)(2005) 57–71.
[15] Henriksson, J. Zhao, H. Dalianis, and H. Bostr ̈om, ―Ensembles of randomized trees using diverse distributed representations of clinical events,‖ (BMC Medical Informatics and Decision Making, 16(2)(2016) 69.
[16] I. Alonso and D. Contreras, ―Evaluation of semantic similarity metrics applied to the automatic retrieval of medical documents: An umls approach,‖ (Expert Systems with Applications, 44(2016) 386–399.
[17] lan H. Witten, ―Text mining‖, University of Waikato, Hamilton, New Zealand.
[18] Johannes C. ScholtesA. Voutilainen.―A syntax-based part of speech analyser‖.In Proc. of the Seventh Conference of the European
[19] Chapter of the Association for Computational Linguistics, pages, Dublin. Association for Computational Linguistics., (1995) 157–164.
[20] Johannes C. Scholtes. ―Text-Mining: The next step in search technology‖, DESI-III Workshop Barcelona, (2009).