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Survey of Text Mining Techniques, Challenges and their Applications

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
N. Venkata Sailaja, L. Padmasree, N. Mangathayaru
10.5120/ijca2016910908

Venkata N Sailaja, L Padmasree and N Mangathayaru. Survey of Text Mining Techniques, Challenges and their Applications. International Journal of Computer Applications 146(11):30-35, July 2016. BibTeX

@article{10.5120/ijca2016910908,
	author = {N. Venkata Sailaja and L. Padmasree and N. Mangathayaru},
	title = {Survey of Text Mining Techniques, Challenges and their Applications},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2016},
	volume = {146},
	number = {11},
	month = {Jul},
	year = {2016},
	issn = {0975-8887},
	pages = {30-35},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume146/number11/25444-2016910908},
	doi = {10.5120/ijca2016910908},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In our everyday life communication interaction among people leading to mutual learning and sharing of valuable knowledge, such as chat, messaging, comments, and posts on board etc. Also, social networking websites, search engines sharing huge data texts in websites. The text is nothing but the combination of characters. Therefore, analyzing and extracting information patterns from such data sets are more complex. Several methods have been proposed for analyzing such texts and extracting information.

In this paper, we present different text mining techniques to discover various textual patterns from the different sources. This topic is also deals with the areas such as information retrieval, machine learning, statistics, computational data sciences and advanced data mining. We also discuss future challenges of this area using different techniques, particularly rough set based text mining techniques, improvements and research directions in this paper.

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Keywords

Data mining, Text mining, Rough sets,Classification, Summarization, and Text categorization.