Abstract :
Named Entity Recognition is the process to detect Named Entities NEs in a file , document or from a corpus and to categorize them into certain Named entity classes like name of city, State, Country, organization, person, location, sport, river, quantity etc. This paper introduces the Named Entities Recognition NER for Myanmar language using Hidden Markov Model HMM .The main idea behind the use of HMM language independent and we can apply this system for any language domain. The corpus used by our NER system is also not domain specific. Khin Khin Lay | Aung Cho "Myanmar Named Entity Recognition with Hidden Markov Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd24012.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/24012/myanmar-named-entity-recognition-with-hidden-markov-model/khin-khin-lay
Keyword :
Named Entity Recognition (NER), Natural Language processing (NLP), Hidden Markov Model (HMM)