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Named Entity Recognition in Natural Language Processing: A Systematic Review

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Proceedings of Second Doctoral Symposium on Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1374))

Abstract

The enormous growth and availability of data poses a great challenge for extracting useful information from documents written in natural language. The information extraction task has become a vital activity in all domains. The process of identifying the names of organization, people, locations or other entities in text is called named entity recognition (NER). It is the subtask and plays an important part to discover and classify the names such as organization name, person name or the location. This is one of the trending fields and most important step in the natural language processing (NLP) for analysis of text. Research on NER changed a lot in the recent decade. NER can consequently examine the entire articles and reveal the individuals, associations, and spots talked about in text. Knowing the applicable labels for every single article help in naturally arranging the articles in all around characterized progressive systems and endorse smooth content disclosure. The pretension of this paper is to present survey on NER. The prime contribution of this research to present state-of-the-art NER is systematically reviewed according to techniques used in NER. This paper also provides tools, datasets, techniques, challenges and future directions in the field of NER with the aim of providing researchers the substantial knowledge for further work.

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Author information

Authors and Affiliations

  1. Computer Science & Engineering, School of Engineering & Technology, Sharda University, Greater Noida, Uttar Pradesh, India

    Abhishek Sharma,  Amrita, Sudeshna Chakraborty & Shivam Kumar

Authors
  1. Abhishek Sharma
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  2. Amrita
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  3. Sudeshna Chakraborty
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  4. Shivam Kumar
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Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. Institute of Engineering and Technology, Lucknow, Uttar Pradesh, India

    Vineet Kansal

  4. University of Calabria, Rende, Cosenza, Italy

    Giancarlo Fortino

  5. Department of Information Technology, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Sharma, A., Amrita, Chakraborty, S., Kumar, S. (2022). Named Entity Recognition in Natural Language Processing: A Systematic Review. In: Gupta, D., Khanna, A., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Second Doctoral Symposium on Computational Intelligence . Advances in Intelligent Systems and Computing, vol 1374. Springer, Singapore. https://doi.org/10.1007/978-981-16-3346-1_66

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