Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval
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 documentar...
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| Format: | Article |
| Language: | fas |
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Babol University of Medical Sciences
2023-05-01
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| Series: | مجله علمسنجی کاسپین |
| Subjects: | |
| Online Access: | http://cjs.mubabol.ac.ir/article-1-305-en.pdf |
| _version_ | 1797316811140628480 |
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| author | Mohammad Hassan Azimi Zeinab Jozi |
| author_facet | Mohammad Hassan Azimi Zeinab Jozi |
| author_sort | Mohammad Hassan Azimi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T03:23:48Z |
| format | Article |
| id | doaj.art-b41693ef1d1f4f1c91b205dfa6893384 |
| institution | Directory Open Access Journal |
| issn | 2423-4710 2383-157X |
| language | fas |
| last_indexed | 2024-03-08T03:23:48Z |
| publishDate | 2023-05-01 |
| publisher | Babol University of Medical Sciences |
| record_format | Article |
| series | مجله علمسنجی کاسپین |
| spelling | doaj.art-b41693ef1d1f4f1c91b205dfa68933842024-02-12T05:55:31ZfasBabol University of Medical Sciencesمجله علمسنجی کاسپین2423-47102383-157X2023-05-011015466Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrievalMohammad Hassan Azimi0Zeinab Jozi1 Department of Knowledge and Information Science, Faculty of Education and Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran Department of Knowledge and Information Science, Faculty of Education and Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran 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.http://cjs.mubabol.ac.ir/article-1-305-en.pdfontologyinformation retrievalknowledge retrievalscientometricsclusteringword co-occurrence |
| spellingShingle | Mohammad Hassan Azimi Zeinab Jozi Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval مجله علمسنجی کاسپین ontology information retrieval knowledge retrieval scientometrics clustering word co-occurrence |
| title | Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval |
| title_full | Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval |
| title_fullStr | Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval |
| title_full_unstemmed | Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval |
| title_short | Scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval |
| title_sort | scientometrics and analysis of thematic clusters of research in the field of ontology in information retrieval |
| topic | ontology information retrieval knowledge retrieval scientometrics clustering word co-occurrence |
| url | http://cjs.mubabol.ac.ir/article-1-305-en.pdf |
| work_keys_str_mv | AT mohammadhassanazimi scientometricsandanalysisofthematicclustersofresearchinthefieldofontologyininformationretrieval AT zeinabjozi scientometricsandanalysisofthematicclustersofresearchinthefieldofontologyininformationretrieval |