The week's pick
Reseach Article
A Survey Report on Text Classification with Different Term Weighing Methods and Comparison between Classification Algorithms
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 75 - Number 7 |
| Year of Publication: 2013 |
| Authors: Anuradha Patra, Divakar Singh |
10.5120/13122-0472
|
Anuradha Patra, Divakar Singh . A Survey Report on Text Classification with Different Term Weighing Methods and Comparison between Classification Algorithms. International Journal of Computer Applications. 75, 7 ( August 2013), 14-18. DOI=10.5120/13122-0472
Abstract
Text classification approach gaining more importance because of the accessibility of large number of electronic documents from a variety of resource. Text categorization is the task of assigning predefined categories to documents. It is the method of finding interesting regularities in large textual, where interesting means non trivial, hidden, previously unknown and potentially useful. The goal of text mining is to enable users to extract information from textual resource and deals with operation such as retrieval, classification, clustering, data mining, natural language preprocessing and machine learning techniques together to classify different pattern. In text classification, term weighting methods design appropriate weights to the given terms to improve the text classification performance. This paper surveys of text classification, process of text classification different term weighing methods and comparisons between different classification algorithms.
References
- Taeho Jo. "Neural Network for text categorization" International Journal of Information Studies 2010
- Gonde Guo, Hui Wang, David Bell,Yaxin Bi and Kieran Greer "KNN Model Based Approach in classification. pp . 986-996 , 2003
- Sebastiani, F. . " Machine Learning in Automated Text Categorization", ACM Computing Survey. pp. 1-47, 2002
- S. N. Sivanandam, S. N. Deepa "Principles of Soft Computing"
- Ramasundram, S. P. Victor "text categorization by BackPropagation" ,Proc. Int'l journal of computer application. pp. 0975-8887, 2010
- Deepika Sharma. "Stemming Algorithms: A Comparative Study and their Analysis" International Journal of Applied Information Systems. September 2012
- Vandana Korde,C Namrata Mahender "Text classification and classifier:A survey" International Journal of Artificial Intelligence & Applications. 2012
- Man Lan, Chew Lim Tan, Jian Su, and Yue Lu. "supervised and traditional term weighing methods for automatic textcategorization" ieee transactions on pattern analysis and machine intelligence. 2009
- Xiaojun Quan, Wenyin Liu, and Bite Qiu May" term weighing schemes for question categorization" ieee transactions on pattern analysis and machine intelligence. 2012
- Z. H. Deng, S. W. Tang, D. Q. Yang, M. Zhang, L. Y. Li, and K. Q. Xie, , "A Comparative Study on Feature Weight in Text Categorization,"Proc. Asia-Pacific Web Conf. pp. 588-597, 2004.
- F. Debole and F. Sebastiani. "Supervised Term Weighting for Automated Text Categorization," Proc. ACM Symp. Applied Computing. pp. 784-788, 2003
- Massand. B, Linoff. G, Waltz. D "Classifying News Stories using Memory based Reasoning", the Proceedings of 15th ACM International Conference on Research and Development in Information Retrieval. pp. 59-65, 1992.
- Yang, YAn evaluation of statistical approaches to text categorization, Information Retrieval. pp67-88. 1999.
- Sebastiani. F, "Machine Learning in Automated Text Categorization", ACM Computing Survey. pp. 1-47, 2002
- SHI Yong-feng, ZHAO, "Comparison of text categorization algorithm", Wuhan university Journal of natural sciences. 2004.
- Joachims, T. "Text Categorization with Support Vector Machines: Learning with many relevantfeatures" europeon conference on machine learning pp 143-151, 1998
- Drucker, H. , Wu, D. , Vapnik, V. N. Support Vector Machines for Spam Categorization, IEEE Transaction on Neural Networks, pp. 1048-1054 1999
- Cristianini. N, Shawe Taylor J. "Support Vector Machines and Other Kernel-based Learning Methods", CambridgeUniversity Press. 2000.
- Wiener E. D. "A Neural Network Approach to Topic Spotting in Text", The Thesis of Master of University of Colorado 1995.
- Ruiz M. E, Srinivasan P. "Hierarchical Text Categorization Using Neural Networks", Information Retrieval, pp 87-118. 2002.
- David D. Lewis and Marc Ringuette, "A comparison of two learning algorithms for text categorization", Proceedings of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval, Las Vegas, US 1994.
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