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A Survey of Text Mining Framework, Methods and Techniques


Affiliations
1 Computer Network and Information Security, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded (M.S.), India
     

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Now-a-days growth of digital data is increasing rapidly. Textual documents created and distributed on the Internet are changing in various forms. All these data or documents are not efficiently useful. We have to analyze large amounts of data in an effort to find correlations, patterns and insights that is nothing but data mining. To discover relationship between two or more variables in data we require data mining. Data mining have attracted huge attention with coming up need for turning such data into knowledge and useful information. Text mining is an important data mining technique. Text mining is one of the recent area for research, is defined as the process of extracting data from large amount of texts. It allows to structure and categorize the textual contents which are initially unstructured.Text mining includes the most successful technique to extract the effective patterns. In this paper we will discuss framework of text mining, techniques and methods to give effectiveness over information extraction in text mining.

Keywords

Data mining, Text Mining, Framework, Methods, Techniques.
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  • Gaikwad, Sonali Vijay, Chaugule, Archana and Patil, Pramod (2014).Text mining methods and techniques. Internat. J. Computer Applic., 85 (17): 42-45.

  • Gupta, Vishal and Lehal, Gurpreet S. (2009).A survey of text mining techniques and applications. J. Emerging Tech. Webintell., 1(1) : 60-76.

  • Haralampos, Karanikas and Babis, Theodoulidis Manchester (2001). Knowledge discovery in text and text mining software?, Centre for Research in Information Management, U.K.

  • Ning, Zhong, Sheng-Tang, Wu and Yuefeng, Li (2012). Effective pattern discovery for text mining. IEEE Trans. Knowl. & Data Engg., 24 :30-44, doi:10.1109/TKDE.2010.211.

  • Shaikh, Mustafa M. Pawar, Ashwini A. and Lahane, Vibha B. (2015). Pattern discovery text mining for document classification. Internat. J. Computer Applic., 117(1):6-12.

  • Sumathy, K.L. and Chidambaram, M. (2013). Text mining: Concepts, applications, tools and issues, An overview. Internat. J. Computer Applic., 80 (4): 29-32.


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  • A Survey of Text Mining Framework, Methods and Techniques

Abstract Views: 774  |  PDF Views: 4

Authors

Yugandhara Bapurao Dasri
Computer Network and Information Security, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded (M.S.), India
Bhagyashree Vyankatrao Barde
Computer Network and Information Security, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded (M.S.), India

Abstract


Now-a-days growth of digital data is increasing rapidly. Textual documents created and distributed on the Internet are changing in various forms. All these data or documents are not efficiently useful. We have to analyze large amounts of data in an effort to find correlations, patterns and insights that is nothing but data mining. To discover relationship between two or more variables in data we require data mining. Data mining have attracted huge attention with coming up need for turning such data into knowledge and useful information. Text mining is an important data mining technique. Text mining is one of the recent area for research, is defined as the process of extracting data from large amount of texts. It allows to structure and categorize the textual contents which are initially unstructured.Text mining includes the most successful technique to extract the effective patterns. In this paper we will discuss framework of text mining, techniques and methods to give effectiveness over information extraction in text mining.

Keywords


Data mining, Text Mining, Framework, Methods, Techniques.

References