IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v119y2019i2d10.1007_s11192-019-03068-1.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03068-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-019-03068-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    2. Wen-Ta Chiu & Yuh-Shan Ho, 2007. "Bibliometric analysis of tsunami research," Scientometrics, Springer;Akadémiai Kiadó, vol. 73(1), pages 3-17, October.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Herman H H B M van Haagen & Peter A C 't Hoen & Barend Mons & Erik A Schultes, 2013. "Generic Information Can Retrieve Known Biological Associations: Implications for Biomedical Knowledge Discovery," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-9, November.
    2. Andrej Kastrin & Dimitar Hristovski, 2021. "Scientometric analysis and knowledge mapping of literature-based discovery (1986–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1415-1451, February.
    3. Yuya Kajikawa, 2022. "Reframing evidence in evidence-based policy making and role of bibliometrics: toward transdisciplinary scientometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5571-5585, September.
    4. Xiangcheng Meng & Alan H. S. Chan, 2021. "Current States and Future Trends in Safety Research of Construction Personnel: A Quantitative Analysis Based on Social Network Approach," IJERPH, MDPI, vol. 18(3), pages 1-17, January.
    5. Dongping Shi & Chengyu Xie & Jinmiao Wang & Lichun Xiong, 2021. "Changes in the Structures and Directions of Heavy Metal-Contaminated Soil Remediation Research from 1999 to 2020: A Bibliometric & Scientometric Study," IJERPH, MDPI, vol. 18(14), pages 1-14, July.
    6. Peng Hui Lv & Gui-Fang Wang & Yong Wan & Jia Liu & Qing Liu & Fei-cheng Ma, 2011. "Bibliometric trend analysis on global graphene research," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 399-419, August.
    7. Su, Hsin-Ning & Lee, Pei-Chun, 2012. "Framing the structure of global open innovation research," Journal of Informetrics, Elsevier, vol. 6(2), pages 202-216.
    8. Zhao, Star X. & Rousseau, Ronald & Ye, Fred Y., 2011. "h-Degree as a basic measure in weighted networks," Journal of Informetrics, Elsevier, vol. 5(4), pages 668-677.
    9. Xingwen Chen & Li Zhu & Chao Liu & Chunhua Chen & Jun Liu & Dongxia Huo, 2023. "Workplace Diversity in the Asia-Pacific Region: A Review of Literature and Directions for Future Research," Asia Pacific Journal of Management, Springer, vol. 40(3), pages 1021-1045, September.
    10. Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.
    11. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    12. Maribel Vega-Arce & Gonzalo Salas & Gastón Núñez-Ulloa & Cristián Pinto-Cortez & Ivelisse Torres Fernandez & Yuh-Shan Ho, 2019. "Research performance and trends in child sexual abuse research: a Science Citation Index Expanded-based analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1505-1525, December.
    13. Ayman Altuwaim & Abdulelah AlTasan & Abdulmohsen Almohsen, 2023. "Success Criteria for Applying Construction Technologies in Residential Projects," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    14. Abderahman Rejeb & Karim Rejeb & Suhaiza Zailani & Yasanur Kayikci & John G. Keogh, 2023. "Examining Knowledge Diffusion in the Circular Economy Domain: a Main Path Analysis," Circular Economy and Sustainability, Springer, vol. 3(1), pages 125-166, March.
    15. Kai Hu & Huayi Wu & Kunlun Qi & Jingmin Yu & Siluo Yang & Tianxing Yu & Jie Zheng & Bo Liu, 2018. "A domain keyword analysis approach extending Term Frequency-Keyword Active Index with Google Word2Vec model," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1031-1068, March.
    16. Yi-Ming Guo & Zhen-Ling Huang & Ji Guo & Hua Li & Xing-Rong Guo & Mpeoane Judith Nkeli, 2019. "Bibliometric Analysis on Smart Cities Research," Sustainability, MDPI, vol. 11(13), pages 1-18, June.
    17. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    18. Ana Batlles-delaFuente & Luis Jesús Belmonte-Ureña & José Antonio Plaza-Úbeda & Emilio Abad-Segura, 2021. "Sustainable Business Model in the Product-Service System: Analysis of Global Research and Associated EU Legislation," IJERPH, MDPI, vol. 18(19), pages 1-33, September.
    19. Yoon, Jisung & Park, Jinseo & Yun, Jinhyuk & Jung, Woo-Sung, 2023. "Quantifying knowledge synchronization with the network-driven approach," Journal of Informetrics, Elsevier, vol. 17(4).
    20. Nikita Jain & Deepali Virmani & Ajith Abraham, 2021. "Tsunami in the last 15 years: a bibliometric analysis with a detailed overview and future directions," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 139-172, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:119:y:2019:i:2:d:10.1007_s11192-019-03068-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.