Knowledge Extraction as an Emerging Discipline: A Bibliographic Analysis
Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJKPS-3-2_001
تاریخ نمایه سازی: 6 تیر 1402
Abstract:
This study aims to conduct a bibliometric analysis of knowledge extraction to examine its grassroots and interdisciplinary interactions based on papers in the Scopus database between ۱۹۸۰ and ۲۰۲۲. The study uses Biblimetrix, performance analysis, and science mapping techniques using ۳۰۷ articles extracted from the Scopus database. The study used Biblimetrix (R package) and VOSviewer as a tool to carry out the performance analysis and science mapping analysis. The results show that the number of publications has significantly increased in the past decade, ۱.۵۳% of authors contribute at least a single article, and ۹۸.۴۶% of authors published multi-authored. China, the USA, and Japan were the most prolific countries in terms of the total number of citations and foreign collaborations. Expert Systems with Applications and the Journal of Knowledge Management are the top journals for knowledge extraction; Advances in Intelligent Systems and Computing (book series), and Lecture Notes in Computer Science are the top conference proceedings series in this field. Implications of knowledge extraction as an emerging discipline have been discussed based on the evidence and trends. The bibliometrics analysis can be helpful for professionals, scholars, and academics interested in bibliometric studies. it also provides essential information for making decisions on the vitality of disciplines.
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Authors
Mila Malekolkalami
Ph.D. Candidate, Knowledge and Information Science-Knowledge Management, Management and Economics faculty, Tarbiat Modares University, Tehran, Iran.
Mohammad Hassanzadeh
Full-Prof., Knowledge and Information Science-Knowledge Management, Management and Economics faculty, Tarbiat Modares University, Tehran, Iran.
Atefeh Sharif
Assistant Prof., Knowledge and Information Science-Knowledge Management, Management and Economics faculty, Tarbiat Modares University, Tehran, Iran
Mansour Rezghi
Associate Professor of Computer Science, Department of Mathematics, Tarbiat Modares University, Tehran, Iran.