Corresponding Author: Zeinab Jozi
Address: Department of Knowledge and Information Science, Faculty of Education and Psychology, Shahid Chamran University of Ahvaz,
Ahvaz, Iran.
E-mail: z-jozi@stu.scu.ac.ir
Scientometrics and analysis of thematic clusters of research in the field of
ontology in information retrieval
Mohammad Hassan Azimi (PhD)
1
, Zeinab Jozi (PhD student)
1
*
1. Department of Knowledge and Information Science, Faculty of Education and Psychology, Shahid Chamran University of
Ahvaz, Ahvaz, Iran.
ABSTRACT
Article Type:
Research Paper
Received:
12 July 2023
Revised:
7 Nov. 2023
Accepted:
11 Nov. 2023
Pub. Online:
21 Nov. 2023
Background and aim: The combination of ontology-based retrieval systems leads to the
semantic retrieval of words. The aim of this study was to review ontology articles in
information retrieval using scientometric techniques.
Materials and methods: The present study was conducted using the documentary method
and word cluster analysis. The research population comprised 2595 articles indexed in
two databases, Scopus and Web of Science, from 2001 to 2023. The data were analyzed
using Excel, BibExcel, SPSS 26 and UCINET. VOSviewer was used to draw research
maps.
Findings: The growth of articles in ontology and information retrieval was low and the
annual growth rate averaged 0.11%.Stanford and California universities were the most
prolific organizations, contributing to 6 articles, and the field of computer science was the
most prolific with 43% of the articles written. The word clustering led to the formation of
4 thematic clusters: semantic retrieval of information, non-human ontology, classification
of systems, and role of technology. In addition, there was a positive correlation between
science production and centralities (degree centrality 0.323, closeness centrality 0.278,
and betweenness centrality 0.447).
Conclusion: The evolution of the words used in the articles has shown that although the
growth of article production in this field has increased from the beginning, the
development of ontology technologies in information retrieval started with a weak
semantic system called information classification, and after the various stages of
development, it now uses machine learning to understand user requirements and process
information with the help of artificial intelligence.
Keywords: Ontology, Information retrieval, Knowledge retrieval, Scientometrics,
Clustering, Word co-occurrence
Cite this article: Azimi MH, Jozi Z. Scientometrics and analysis of thematic clusters of research in the field of
ontology in information retrieval. Caspian Journal of Scientometrics. 2023; 10(1): 54-66.
© The Author(s).
Publisher: Babol University of Medical Sciences
[ DOI: 10.22088/cjs.10.1.54 ] [ Downloaded from cjs.mubabol.ac.ir on 2024-01-17 ]
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