Paper Title
Hindi Named Entities Recognition (NER) using Natural Language Processing and Machine Learning

Abstract
Named Entity Recognition (NER) is an important task in Natural Language Processing (NLP) that aims to auto identify and annotate Named Entities in the text, such as Person, Location, Organization etc. NER has been an essential component in various applications such as Information Extraction and Retrieval, Machine Translation, Question Answering (Q-A), Text Summarization etc. For NER in Hindi, while there have been a number of studies carried out, no high accuracy tool has yet been developed as per the Literature Survey. In this research, a methodology for Hindi Named Entities Recognition using NLP algorithms with RDF and Conditional Random Fields has been proposed. The results derived shows that the hybrid approach for NER achieves the recognition accuracy to 90.7% on Hindi texts. Keywords - Named Entity Recognition, Machine Learning, Natural Language Processing, CRF

Author - Ria Mehta, Dweep Pandya, Pratik Chaudhari, Devika Verma,Krishnanjan Bhattacharjee, Shiva Karthik S, Swati Mehta, Ajai Kumar

Published : Volume-6,Issue-9  ( Sep, 2019 )

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