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.
