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A new method for automatically constructing domain-oriented term taxonomy based on weighted word co-occurrence analysis

Author

Listed:
  • Shuqing Li

    (College of Information Engineering)

  • Ying Sun

    (University at Buffalo, The State University of New York)

  • Dagobert Soergel

    (University at Buffalo, The State University of New York)

Abstract

The automatically construction of term taxonomy can enhance our ability for expressing the science mapping. In this paper, we introduce the definition of weighted co-occurring word pair and corresponding improved method of word co-occurrence analysis. An application and evaluation of this proposed method in the library and information science is also discussed, which includes how to get the expanded effective keywords, how to calculate the weight of keywords and their relations, and how to abstract the hierarchical structures and other relations such as synonyms and etc. A visualization tool and a prototype search system are designed for browsing the term taxonomy identified. Finally, we report the experiment of evaluation and comparison. The experiment results prove that this proposed method in helping users doing semantic searches and expanding their searching results is effective and can meet the requirement of some specific domains.

Suggested Citation

  • Shuqing Li & Ying Sun & Dagobert Soergel, 2015. "A new method for automatically constructing domain-oriented term taxonomy based on weighted word co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1023-1042, June.
    • Handle: RePEc:spr:scient:v:103:y:2015:i:3:d:10.1007_s11192-015-1571-0
    DOI: 10.1007/s11192-015-1571-0
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    References listed on IDEAS

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    Cited by:

    1. Tingting Zhang & Baozhen Lee & Qinghua Zhu, 2019. "Semantic measure of plagiarism using a hierarchical graph model," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 209-239, October.
    2. Xicheng Yin & Hongwei Wang & Pei Yin & Hengmin Zhu & Zhenyu Zhang, 2020. "A co-occurrence based approach of automatic keyword expansion using mass diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1885-1905, September.
    3. Abolghasem Arabiun & Niloofar Salajegheh & Zeynab Aeeni & Armin Khaleghi Forghani, 2023. "Trends and patterns in entrepreneurial action research: a bibliometric overview and research agenda," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 13(1), pages 1-17, December.

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