CFP last date
22 April 2024
Reseach Article

Text Mining Methods and Techniques

by Sonali Vijay Gaikwad, Archana Chaugule, Pramod Patil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 17
Year of Publication: 2014
Authors: Sonali Vijay Gaikwad, Archana Chaugule, Pramod Patil
10.5120/14937-3507

Sonali Vijay Gaikwad, Archana Chaugule, Pramod Patil . Text Mining Methods and Techniques. International Journal of Computer Applications. 85, 17 ( January 2014), 42-45. DOI=10.5120/14937-3507

@article{ 10.5120/14937-3507,
author = { Sonali Vijay Gaikwad, Archana Chaugule, Pramod Patil },
title = { Text Mining Methods and Techniques },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 17 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 42-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number17/14937-3507/ },
doi = { 10.5120/14937-3507 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:02:45.391276+05:30
%A Sonali Vijay Gaikwad
%A Archana Chaugule
%A Pramod Patil
%T Text Mining Methods and Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 17
%P 42-45
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years growth of digital data is increasing, knowledge discovery and data mining have attracted great attention with coming up need for turning such data into useful information and knowledge. The use of the information and knowledge extracted from a large amount of data benefits many applications like market analysis and business management. In many applications database stores information in text form so text mining is the one of the most resent area for research. To extract user required information is the challenging issue. Text Mining is an important step of knowledge discovery process. Text mining extracts hidden information from not-structured to semi-structured data. Text mining is the discovery by automatically extracting information from different written resources and also by computer for extracting new, previously unknown information. This survey paper tries to cover the text mining techniques and methods that solve these challenges. In this survey paper we discuss such successful techniques and methods to give effectiveness over information retrieval in text mining. The types of situations where each technology may be useful in order to help users are also discussed.

References
  1. G. Salton and C. Buckley, "Term-Weighting Approaches in Automatic Text Retrieval," Information Processing and Management:An Int'l J. , vol. 24, no. 5, pp. 513-523, 1988.
  2. H. Ahonen, O. Heinonen, M. Klemettinen, and A. I. Verkamo, "Applying Data Mining Techniques for Descriptive Phrase Extraction in Digital Document Collections," Proc. IEEE Int'l Forum on Research and Technology Advances in Digital Libraries (ADL '98), pp. 2-11, 1998.
  3. W. Lam, M. E. Ruiz, and P. Srinivasan, "Automatic Text Categorization and Its Application to Text Retrieval," IEEE Trans. Knowledge and Data Eng. , vol. 11, no. 6, pp. 865-879, Nov. /Dec. 1999.
  4. H. Lodhi, C. Saunders, J. Shawe-Taylor, N. Cristianini, and C. Watkins, "Text Classification Using String Kernels," J. Machine Learning Research, vol. 2, pp. 419-444, 2002.
  5. S. -T. Wu, Y. Li, Y. Xu, B. Pham, and P. Chen, "Automatic Pattern- Taxonomy Extraction for Web Mining," Proc. IEEE/WIC/ACM Int'l Conf. Web Intelligence (WI '04), pp. 242-248, 2004.
  6. S. -T. Wu, Y. Li, and Y. Xu, "Deploying Approaches for Pattern Refinement in Text Mining," Proc. IEEE Sixth Int'l Conf. Data Mining (ICDM '06), pp. 1157-1161, 2006.
  7. S. Shehata, F. Karray, and M. Kamel, "Enhancing Text Clustering Using Concept-Based Mining Model," Proc. IEEE Sixth Int'l Conf. Data Mining (ICDM '06), pp. 1043-1048, 2006.
  8. S. Shehata, F. Karray, and M. Kamel, "A Concept-Based Model for Enhancing Text Categorization," Proc. 13th Int'l Conf. Knowledge Discovery and Data Mining (KDD '07), pp. 629-637, 2007
Index Terms

Computer Science
Information Sciences

Keywords

Text mining process methods technologies