An Efficient Hindi Text Classification Model Using SVM

摘要: In today’s world, several digitized Hindi text documents are generated daily at the Government sites, news portals, and public private sectors, which required to be classified effectively into various mutually exclusive pre-defined categories. As such, many text-based processing systems exist in application domains of information retrieval, machine translation, summarization, simplification, keyword extraction, other related parsing linguistic perspectives, but still, there is a wide scope classify extracted categories using classifier. this paper, Text Classification model proposed, accepts set known documents, preprocesses them document, sentence word levels, extracts features, trains SVM classifier, further classifies unknown documents. Such classification becomes challenging due its large available conjuncts letter combinations, structure, multisense words. The experiments have been performed on four two categories, by with 100% accuracy.