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Generating a representative keyword subset pertaining to an academic conference series

Author

Listed:
  • Agniv Adhikari

    (CSIR-Central Glass & Ceramic Research Institute)

  • Paramita Das

    (Indian Institute of Engineering Science and Technology)

  • Abhik Mukherjee

    (Indian Institute of Engineering Science and Technology)

Abstract

The breadth and velocity of innovation has resulted in explosion of research documents day by day. Academic conferences are being arranged worldwide, most of them in regular intervals, thereby generating a huge volume of research documents. Extracting undiscovered knowledge from the conference papers and thereby finding the inter-relationship of conference research topics is a challenging task. This paper attempts towards knowledge discovery for the conference with the help of keywords mentioned in the papers presented therein. The scheme proposed here tries to include the entire set of conference research papers using a small subset of all available keywords. The correctness and complexity of the scheme are analyzed. Proof of concept is established through some flagship conference held annually round the globe. The performance is favourable when compared with available text mining methods, as far as practicable. Results indicate that the scheme could be useful in characterizing topical themes of academic conferences, which may benefit both participants and organizers.

Suggested Citation

  • Agniv Adhikari & Paramita Das & Abhik Mukherjee, 2019. "Generating a representative keyword subset pertaining to an academic conference series," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 749-770, May.
    • Handle: RePEc:spr:scient:v:119:y:2019:i:2:d:10.1007_s11192-019-03068-1
    DOI: 10.1007/s11192-019-03068-1
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    References listed on IDEAS

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    1. Neil R. Smalheiser, 2012. "Literature‐based discovery: Beyond the ABCs," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(2), pages 218-224, February.
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    3. Neil R. Smalheiser, 2012. "Literature-based discovery: Beyond the ABCs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 218-224, February.
    4. Hsin-Ning Su & Pei-Chun Lee, 2010. "Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 65-79, October.
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