Approaches to Named Entity Recognition


Authors : Dr. A Debbarma

Volume/Issue : Volume 8 - 2023, Issue 12 - December

Google Scholar : http://tinyurl.com/4pvfpms8

Scribd : http://tinyurl.com/ezs78akx

DOI : https://doi.org/10.5281/zenodo.10464719

Abstract : This study explores the evolution of Named Entity Recognition (NER) methods, encompassing rule- based, machine learning-based, and hybrid approaches. It emphasizes the significance of NER in North East India's linguistically diverse context, revealing digital disparities. Despite the region's modest size, NER initiatives have emerged for languages like Assamese, Manipuri, Mizo, and Kokborok. The journey spans rule-based systems to advanced machine learning techniques, highlighting the dynamic nature of the field. Successful hybrid approaches, combining rule-based and machine learning methods, are showcased. However, digital disparities persist, underscoring the need for continued research and technological advancements to bridge gaps in North East India's linguistic diversity.

Keywords : NLP, NER, Rule-based, ML, NER.

This study explores the evolution of Named Entity Recognition (NER) methods, encompassing rule- based, machine learning-based, and hybrid approaches. It emphasizes the significance of NER in North East India's linguistically diverse context, revealing digital disparities. Despite the region's modest size, NER initiatives have emerged for languages like Assamese, Manipuri, Mizo, and Kokborok. The journey spans rule-based systems to advanced machine learning techniques, highlighting the dynamic nature of the field. Successful hybrid approaches, combining rule-based and machine learning methods, are showcased. However, digital disparities persist, underscoring the need for continued research and technological advancements to bridge gaps in North East India's linguistic diversity.

Keywords : NLP, NER, Rule-based, ML, NER.

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