Approaches to Named Entity Recognition in Indian Languages: A Study
Prakash Hiremath1, Shambhavi B. R2
1Prakash Hiremath, M. Tech Student, Department of Information Science and Engineering, B. M. S. College of Engineering, Bangalore, India.
2Dr. Shambhavi B. R, Assoc. Prof, Department of Information Science and Engineering, B. M. S. College of Engineering, Bangalore, India.
Manuscript received on July 21, 2014. | Revised Manuscript received on August 06, 2014. | Manuscript published on August 30, 2014. | PP: 191-194 | Volume-3 Issue-6, August 2014. | Retrieval Number: F3385083614/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Named Entity Recognition (NER) is subtask of information extraction that seeks to locate and classify the elements in some text into pre-defined categories. NER finds its application in Natural Language Processing tasks like machine translation, question-answering systems and automatic summarization. The approaches to NER are rule based, statistics based or a combination of both. In this paper, we present a survey of these various approaches for identification of Names Entities (NE) in Indian Languages.
Keywords: Named Entity Recognition (NER), Natural Language Processing, Machine Learning.