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DOI: 10.14569/IJACSA.2016.071153
PDF

Text Mining: Techniques, Applications and Issues

Author 1: Ramzan Talib
Author 2: Muhammad Kashif Hanif
Author 3: Shaeela Ayesha
Author 4: Fakeeha Fatima

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 11, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Rapid progress in digital data acquisition tech-niques have led to huge volume of data. More than 80 percent of today’s data is composed of unstructured or semi-structured data. The discovery of appropriate patterns and trends to analyze the text documents from massive volume of data is a big issue. Text mining is a process of extracting interesting and non-trivial patterns from huge amount of text documents. There exist different techniques and tools to mine the text and discover valuable information for future prediction and decision making process. The selection of right and appropriate text mining technique helps to enhance the speed and decreases the time and effort required to extract valuable information. This paper briefly discuss and analyze the text mining techniques and their applications in diverse fields of life. Moreover, the issues in the field of text mining that affect the accuracy and relevance of results are identified.

Keywords: Classification; Knowledge Discovery; Applications; Information Extraction; Patterns

Ramzan Talib, Muhammad Kashif Hanif, Shaeela Ayesha and Fakeeha Fatima, “Text Mining: Techniques, Applications and Issues” International Journal of Advanced Computer Science and Applications(IJACSA), 7(11), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071153

@article{Talib2016,
title = {Text Mining: Techniques, Applications and Issues},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071153},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071153},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {11},
author = {Ramzan Talib and Muhammad Kashif Hanif and Shaeela Ayesha and Fakeeha Fatima}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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