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A Survey on Domain-Specific Summarization Techniques

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Advances in Data and Information Sciences

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 318))

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Abstract

Automatic text summarization using different natural language processing techniques (NLP) has gained much momentum in recent years. Text summarization is an intensive process of extracting representative gist of the contents present in a document. Manual summarization of structured and unstructured text is a tedious task that involves immense human effort and time. There are quite a number of successful text summarization algorithms for generic documents. But when it comes specialized for a particular domain, the generic training of algorithms does not suffice the purpose. Hence, context-aware summarization of unstructured and structured text using various algorithms needs specific scoring techniques to supplement the base algorithms. This paper is an attempt to give an overview of methods and algorithms that are used for context-aware summarization of generic texts.

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Authors and Affiliations

  1. Christ Deemed to be University, Bangalore, Karnataka, India

    Reshmi P. Rajan & Deepa V. Jose

Authors
  1. Reshmi P. Rajan
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  2. Deepa V. Jose
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Corresponding author

Correspondence to Reshmi P. Rajan .

Editor information

Editors and Affiliations

  1. Krishna Engineering College, Ghaziabad, India

    Shailesh Tiwari

  2. National Institute of Technology Agartala, Agartala, Tripura, India

    Munesh C. Trivedi

  3. Department of Engineering and Science, University of Agder, Kristiansand, Norway

    Mohan Lal Kolhe

  4. Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

    K.K. Mishra

  5. Department of Computer Science and Engineering, RBS Engineering Technical Campus, Agra, Uttar Pradesh, India

    Brajesh Kumar Singh

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Rajan, R.P., Jose, D.V. (2022). A Survey on Domain-Specific Summarization Techniques. In: Tiwari, S., Trivedi, M.C., Kolhe, M.L., Mishra, K., Singh, B.K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 318. Springer, Singapore. https://doi.org/10.1007/978-981-16-5689-7_31

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