Domain Specific Named Entity Recognition Using Natural Language Processing (NLP) and Software Engineering in Production World

Author(s)	Bickey Kumar Shah, Prince Kumar
Country	India
Abstract	This research is concerned with domain-specific named entity recognition in which certain keywords are withdrawn from the phrase and sentences of the words or paragraph. The project in hand has been effective in different sectors like the insurance companies and hospitals for withdrawing the required keywords in a small amount of time. For instance, a medicine that belongs to a specific keyword is extracted easily and the same occurs with necessary keywords in the case of insurance companies. Advancements in deep neural networks have been established to build the named entity recognition model (NER Model). We have used Spacy and natural language processing for keyword extraction. The future scope of the project is to use LSTM for domain-specific keyword extraction and transfer learning using NLP. A large dataset is required to build the system for keyword extraction since dataset have always been the challenging part of such a system.
Keywords	NER, LSTM, NLP
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-05-19
Cite This	Domain Specific Named Entity Recognition Using Natural Language Processing (NLP) and Software Engineering in Production World - Bickey Kumar Shah, Prince Kumar - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.21037
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.21037
Short DOI	https://doi.org/gtvtwb

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International Journal For Multidisciplinary Research