Generating a representative keyword subset pertaining to an academic conference series

Agniv Adhikari (), Paramita Das () and Abhik Mukherjee ()
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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

Scientometrics, 2019, vol. 119, issue 2, No 9, 749-770

Abstract: 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.

Keywords: Text mining; Knowledge discovery; Greedy algorithms; Computational complexity; Heuristic algorithms; Knowledge representation (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11192-019-03068-1

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