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Co-Occurrence-Based Double Thresholding Method for Research Topic Identification

Author

Listed:
  • Christian-Daniel Curiac

    (Department of Computer and Information Technology, Politehnica University of Timisoara, V. Parvan 2, 300223 Timisoara, Romania)

  • Alex Doboli

    (Department of Electrical and Computer Engineering, Stony Brook University, State University of New York, Stony Brook, NY 11794-2350, USA)

  • Daniel-Ioan Curiac

    (Department of Automation and Applied Informatics, Politehnica University of Timisoara, V. Parvan 2, 300223 Timisoara, Romania)

Abstract

Identifying possible research gaps is a main step in problem framing, however it is increasingly tedious and expensive considering the continuously growing amount of published material. This situation suggests the critical need for methodologies and tools that can assist researchers in their selection of future research topics. Related work mostly focuses on trend analysis and impact prediction but less on research gap identification. This paper presents our first approach in automated identification of feasible research gaps by using a double-threshold procedure to eliminate the research gaps that are currently difficult to study or offer little novelty. Gaps are then found by extracting subgraphs for the less-frequent co-occurrences and correlations of key terms describing domains. A case study applying the methodology for electronic design automation (EDA) domain is also discussed in the paper.

Suggested Citation

  • Christian-Daniel Curiac & Alex Doboli & Daniel-Ioan Curiac, 2022. "Co-Occurrence-Based Double Thresholding Method for Research Topic Identification," Mathematics, MDPI, vol. 10(17), pages 1-10, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:17:p:3115-:d:901955
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    References listed on IDEAS

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    1. Liu, Xiang & Jiang, Tingting & Ma, Feicheng, 2013. "Collective dynamics in knowledge networks: Emerging trends analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 425-438.
    2. Francisco Muñoz-Leiva & María Viedma-del-Jesús & Juan Sánchez-Fernández & Antonio López-Herrera, 2012. "An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longitudinal perspective," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(4), pages 1077-1095, June.
    3. Akimushkin, Camilo & Amancio, Diego R. & Oliveira, Osvaldo N., 2018. "On the role of words in the network structure of texts: Application to authorship attribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 49-58.
    4. S. Phineas Upham & Henry Small, 2010. "Emerging research fronts in science and technology: patterns of new knowledge development," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 15-38, April.
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