A Survey on Various Approaches Used in Named Entity Recognition for Indian Languages
Article No.: 55, Pages 1 - 5
Abstract
Named Entity Recognition (NER)” is a application of Artificial Intelligence, Machine Learning and “Natural Language Processing (NLP”).In NER, various classes of Named entity such as name of a person, an organization name, name of location, name of designation etc., are find out which is required in many NLP activities like question-answering system,machine translation, artificial intelligence, summarization of documents, academics, robotics, Bioinformatics etc. Mostly NER task was evident for foreign languages but for Indian constitutional languages, due to some challenges present for example scarcity of resources, ambiguity present in languages, morphologically rich behavior of languages etc.,NER work has been done for few of languages. In our paper, we presented several challenges available in NER for Indian languages and compared them by measuring various standard evaluation metric values like precision, recall and F-measure. In future extension, we would develop a efficient system, which would be more accurate, and which will cater many more Named Entity tags than existing systems,for Indian languages NER tools.
References
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Published In
December 2022
749 pages
ISBN:9781450399937
DOI:10.1145/3590837
Copyright © 2022 ACM.
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Published: 30 May 2023
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ICIMMI 2022
ICIMMI 2022: International Conference on Information Management & Machine Intelligence
December 23 - 24, 2022
Jaipur, India
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