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A Survey on Acronym–Expansion Mining Approaches from Text and Web

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Smart Intelligent Computing and Applications

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 104))

Abstract

An acronym is a textual form used to refer an entity and to stress the important concepts. Over the last two decades, many researchers worked for mining acronym expansion pairs from plain text and Web. This is mainly used in language processing, information retrieval, Web search, ontology mapping, question answering, SMS, and social media posting. Acronyms are dynamically growing day by day, and discovering its definition/expansion is becoming a challenging task because of its diversified characteristics. Manually edited online repositories have acronym definition pairs, but it is an overwhelming task to update all possible definitions systematically. To extend the support, different approaches are employed for the automatic detection of acronym definitions from text and Web documents. This paper presents those approaches and also reveals the Web-based methods used for disambiguating, ranking, finding popularity score, and context words of the expansions. The scope for the future work in this research area is also conferred in this paper.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Dr. Mahalingam College of Engineering & Technology, Pollachi, Tamil Nadu, India

    R. Menaha

  2. Department of Electronics and Communication Engineering, PSNA College of Engineering & Technology, Dindigul, Tamil Nadu, India

    VE. Jayanthi

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  1. R. Menaha
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  2. VE. Jayanthi
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Correspondence to R. Menaha .

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Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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Menaha, R., Jayanthi, V. (2019). A Survey on Acronym–Expansion Mining Approaches from Text and Web. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 104. Springer, Singapore. https://doi.org/10.1007/978-981-13-1921-1_12

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  • DOI: https://doi.org/10.1007/978-981-13-1921-1_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1920-4

  • Online ISBN: 978-981-13-1921-1

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