Semantic technologies and information retrieval: : research trends and directions in Iran

Document Type : Original Article

Authors

1 Professor, Department of Knowledge and Information science, University of Qom, Qom, Iran;

2 Assistant Professor, Shahid Beheshti University, Tehran, Iran

3 Ph.D. in Knowledge and Information Science, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

4 M.Sc. in Knowledge and Information Science, University of Qom, Qom, Iran

Abstract

Objective: The present study aims to identify scientific products of information retrieval and semantic technologies within Persian databases and to analyze these studies through a systematic review. Information retrieval is a crucial and foundational topic in library and information sciences, while the semantic web is a core area within retrieval and knowledge management. The large volume of research in semantic technologies shows the importance of analyzing and surveying the scientific products of this field. Analyzing the scientific products of the field of semantic technologies
and information retrieval determines the trends and tendencies of studies in this field and guides researchers for future research.
Method: The present study was conducted using a systematic review method. The stages of the study are as follows: The first stage involved determining and identifying the research questions. The second stage focused on developing the resource search strategy, which included criteria for including and excluding resources, identifying databases, selecting keywords, and employing complementary methods for resource identification. The third stage involves the critical appraisal of resources, including abstracts and full texts, while the fourth stage focuses on analyzing and synthesizing these resources. Persian databases used in the search include the Iranian Research Institute for Information Science and Technology (Irandoc), Megiran, the Scientific Information Database (SID), the Noor Specialized Magazines website (Noormagz), and Civlica. The search employed keywords such as "semantic technologies" and "semantic web" combined with "information retrieval"; "search engines, and "libraries" combined with "semantic web"; and, among semantic web technologies, ontology, RDF, and linked data in combination with "information retrieval" were used for the search.
Findings: Scientific productions in the fields of information retrieval and semantic technologies were classified into two categories based on research methodology: research studies and review studies. Out of the 165 identified sources, 119 were classified as research studies, and 46 were categorized as review studies. The research studies were further divided into six groups: ontology (design, application, and evaluation), SPARQL, linked data, semantic search engines, and various semantic technologies. Among these, 71 research studies focused specifically on the design, application, and evaluation of ontologies. The review studies were categorized into four groups: information and knowledge organization, information retrieval, information and retrieval systems,
and other related topics. Within the review studies, most resources concentrated on information
and knowledge organization, with ontology being discussed more extensively than other semantic technologies.
Conclusion: Although the majority of studies have focused on ontology, there remains a need for further research on the design, development, and application of ontologies across various disciplines and information storage and retrieval systems. Furthermore, additional studies are required on semantic technologies to clarify the role of each technology in information retrieval. Given that many studies have employed proposed methods, architectures, frameworks, and their evaluation through empirical approaches, conducting research in this area demands technical expertise. Therefore, collaboration between information technology specialists and experts from other fields can effectively enrich research and guide its application in practical systems. Additionally, researchers should prioritize studies in the area of semantic image retrieval. Overall, this review aims to provide a clear and comprehensive overview of the field by examining the scientific literature on semantic technologies and image information retrieval.

Keywords

Main Subjects

References

Bashir, F., & Warraich, N. F. (2023). Systematic literature review of Semantic Web for distance learning. Interactive Learning Environments, 31(1), 527-543.             
https://doi.org/10.1080/10494820.2020.1799023
Haque, A. K. M., Arifuzzaman, B. M., Siddik, S. A. N., Kalam, A., Shahjahan, T. S., Saleena, T. S., ... & Hossain, M. J. (2022). Semantic web in healthcare: a systematic literature review of application, research gap, and future research avenues. International Journal of Clinical Practice, 2022. https://doi.org/10.1155/2022/6807484
Huiping, J. (2010, September). Information Retrieval and the semantic web. In 2010 International Conference on Educational and Information Technology (Vol. 3, pp. V3-461). IEEE.    
https://doi.org/10.1109/ICEIT.2010.5607549
Mithun, A. M., & Bakar, Z. A. (2020). Empowering information retrieval in semantic web. International Journal of Computer Network and Information Security, 12(2), 41-48.
https://doi.org/10.5815/ijcnis.2020.02.05
Rhayem, A., Mhiri, M. B. A., & Gargouri, F. (2020). Semantic web technologies for the internet of things: Systematic literature review. Internet of Things, 11, 100206.
https://doi.org/10.1016/j.iot.2020.100206
Thangaraj, M., & Sujatha, G. (2014). An architectural design for effective information retrieval in semantic web. Expert Systems with Applications, 41(18), 8225-8233.
https://doi.org/10.1016/j.eswa.2014.07.017
Send comment about this article
CAPTCHA Image
Sciences and Techniques of Information Management
Volume 11, Issue 2
July 2025
Pages 319-360

Files

Share

How to cite

Statistics