Named entity recognition approaches: A study applied to English and Hindi language

2015 ◽  
Author(s):  
Gowri Prasad ◽  
K. K. Fousiya
Keyword(s):  
Named Entity Recognition ◽  
Entity Recognition ◽  
Named Entity ◽  
Hindi Language

Named Entity System for Tweets in Hindi Language

2018 ◽  
Vol 14 (4) ◽  
pp. 55-76 ◽  
Author(s):  
Arti Jain ◽  
Anuja Arora
Keyword(s):  
Conditional Random Field ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Processing Stage ◽  
Learning Stage ◽  
Named Entity ◽  
Health Related ◽  
Hindi Language ◽  
Demand For Health ◽  
Health Applications

Due to the growing need of smart-health applications in Hindi language, there is a rapid demand for health-related Named Entity Recognition (NER) system for Hindi. For the purpose of the same, this research considers Twitter social network to extract tweets dated 1st October 2016 to 15th October 2017 from Patanjali, Dabur and other Hindi language-oriented Twitter based health sites; while considering four NE types- Person, Disease, Consumable and Organization. To the best of its knowledge, the considered Twitter dataset and NE types for Hindi language is one of the first resources that is being taken care. This article introduces three stage NER system for Tweets in Hindi language (HinTwtNER system)- pre-processing stage; machine Learning stage (Hyperspace Analogue to Language (HAL) and Conditional Random Field (CRF)); and post-processing stage. HinTwtNER looks into binary features and achieves an overall F-score of 49.87% which is comparable to the Twitter based NER systems for English and other languages.

A deep neural network-based model for named entity recognition for Hindi language

2020 ◽  
Vol 32 (20) ◽  
pp. 16191-16203
Author(s):  
Richa Sharma ◽  
Sudha Morwal ◽  
Basant Agarwal ◽  
Ramesh Chandra ◽  
Mohammad S. Khan
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Named Entity ◽  
Hindi Language
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