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首页> 外文期刊>International Journal of Rough Sets and Date Analysis >Hindi Text Document Classification System Using SVM and Fuzzy: A Survey
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Hindi Text Document Classification System Using SVM and Fuzzy: A Survey

机译:基于SVM和Fuzzy的印地语文本文档分类系统:一项调查

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摘要

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.
机译:近年来,在梵文,尤其是北印度文中,针对不同的领域提出了许多信息检索,字符识别和特征提取方法。由于巨大的扫描数据可用性并为光学字符识别之外的现有印地语自动化系统提供了先进的改进,因此引入了使用支持向量机和模糊逻辑的印地语打印和手写文档分类系统的新思想。这首先进行预处理,然后将文本图像文档分类为预定义的类别。以此概念为基础,本文描述了与印地语相关性的此类系统的可行性研究,从不同来源获得的印地语关键字统计测量结果的调查报告,以及在印刷和手写文档中发现的固有挑战。提供了技术评审并以图形方式表示,以比较许多参数并估计各种现有技术中使用的内容,形式和分类器。

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