Document Type : Research Paper
Authors
1 Knowledge and Information Science Dept., Faculty of Management, University of Tehran, Tehran, Iran
2 Deputy Assistant of Archives, Islamic Revolution Document Center of Iran
3 Artificial Intelligence and Robotics Depart., Faculty of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract
Abstract
Organizing information in digital archives, particularly historical ones such as the Islamic Revolution Document Center of Iran, faces challenges like the inefficiency of traditional information retrieval systems. This center, with over 4.5 million document pages, 31 thousand hours of oral history, and millions of news titles and articles, requires innovative approaches such as domain ontology and knowledge graphs to improve semantic access to key entities. The aim of this research is to model a domain ontology for the digital archive of this center using a hybrid approach of text analysis and reuse of existing ontologies. The research method is mixed: semi-automatic and automatic text analysis for entity extraction, model design based on ontology principles, and validation of findings using the nominal group technique. The findings include 535 classes that, after validation with criteria of 1) hierarchical logic, 2) historical/cultural accuracy, 3) alignment and equivalence, and 4) completeness and simplicity, resulted in 457 classes confirmed, 70 classes added, 53 classes relocated in the hierarchy, and 19 classes removed. This ontology provides a foundation for a knowledge graph, enhances semantic retrieval, and serves as a logical basis for artificial intelligence systems in managing Iran's historical documents. This research fills the gap in designing practical ontologies for contemporary Iranian history and is extensible to similar domains.
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