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DOI: 10.14569/IJACSA.2011.021119
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A Fuzzy Similarity Based Concept Mining Model for Text Classification

Author 1: Shalini Puri

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 2 Issue 11, 2011.

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Abstract: Text Classification is a challenging and a red hot field in the current scenario and has great importance in text categorization applications. A lot of research work has been done in this field but there is a need to categorize a collection of text documents into mutually exclusive categories by extracting the concepts or features using supervised learning paradigm and different classification algorithms. In this paper, a new Fuzzy Similarity Based Concept Mining Model (FSCMM) is proposed to classify a set of text documents into pre - defined Category Groups (CG) by providing them training and preparing on the sentence, document and integrated corpora levels along with feature reduction, ambiguity removal on each level to achieve high system performance. Fuzzy Feature Category Similarity Analyzer (FFCSA) is used to analyze each extracted feature of Integrated Corpora Feature Vector (ICFV) with the corresponding categories or classes. This model uses Support Vector Machine Classifier (SVMC) to classify correctly the training data patterns into two groups; i. e., + 1 and – 1, thereby producing accurate and correct results. The proposed model works efficiently and effectively with great performance and high - accuracy results.

Keywords: Text Classification; Natural Language Processing; Feature Extraction; Concept Mining; Fuzzy Similarity Analyzer; Dimensionality Reduction; Sentence Level; Document Level; Integrated Corpora Level Processing.

Shalini Puri, “ A Fuzzy Similarity Based Concept Mining Model for Text Classification” International Journal of Advanced Computer Science and Applications(IJACSA), 2(11), 2011. http://dx.doi.org/10.14569/IJACSA.2011.021119

@article{Puri2011,
title = { A Fuzzy Similarity Based Concept Mining Model for Text Classification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.021119},
url = {http://dx.doi.org/10.14569/IJACSA.2011.021119},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {11},
author = {Shalini Puri}
}



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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