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Hindi Text Document Classification System Using SVM and Fuzzy: A Survey

Shalini Puri, Satya Prakash Singh

Source Title: International Journal of Rough Sets and Data Analysis (IJRSDA)5(4)

ISSN: 2334-4598|EISSN: 2334-4601|EISBN13: 9781522547044|DOI: 10.4018/IJRSDA.2018100101

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MLA

Puri, Shalini, and Satya Prakash Singh. "Hindi Text Document Classification System Using SVM and Fuzzy: A Survey." IJRSDA vol.5, no.4 2018: pp.1-31. http://doi.org/10.4018/IJRSDA.2018100101

APA

Puri, S. & Singh, S. P. (2018). Hindi Text Document Classification System Using SVM and Fuzzy: A Survey. International Journal of Rough Sets and Data Analysis (IJRSDA), 5(4), 1-31. http://doi.org/10.4018/IJRSDA.2018100101

Chicago

Puri, Shalini, and Satya Prakash Singh. "Hindi Text Document Classification System Using SVM and Fuzzy: A Survey," International Journal of Rough Sets and Data Analysis (IJRSDA) 5, no.4: 1-31. http://doi.org/10.4018/IJRSDA.2018100101

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Abstract

In recent years, many information retrieval, character recognition, and feature extraction methodologies in Devanagari and especially in Hindi have been proposed for different domain areas. Due to enormous scanned data availability and to provide an advanced improvement of existing Hindi automated systems beyond optical character recognition, a new idea of Hindi printed and handwritten document classification system using support vector machine and fuzzy logic is introduced. This first pre-processes and then classifies textual imaged documents into predefined categories. With this concept, this article depicts a feasibility study of such systems with the relevance of Hindi, a survey report of statistical measurements of Hindi keywords obtained from different sources, and the inherent challenges found in printed and handwritten documents. The technical reviews are provided and graphically represented to compare many parameters and estimate contents, forms and classifiers used in various existing techniques.

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Hindi Text Document Classification System Using SVM and Fuzzy: A Survey

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