Designing Ontology and Knowledge Graph for Cognitive Warfare: An AI-Based Approach

سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 53

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شناسه ملی سند علمی:

ICAII01_060

تاریخ نمایه سازی: 19 اسفند 1403

چکیده مقاله:

The aim of this study is to design an ontology and a knowledge graph for cognitive warfare based on artificial intelligence (AI) technologies. This applied research employed a qualitative content analysis method to extract key concepts and semantic relationships in the domain of cognitive warfare. The data collection tool was a checklist containing identified concepts and relationships for designing the ontology and knowledge graph of cognitive warfare. In this study, to design the knowledge graph for cognitive warfare, the required entities for semantic representation in the domain of cognitive warfare were first identified using AI technologies such as ChatGPT, Gemini, and Copilot. At this stage, after aggregation, refinement, and editing of the entities by the researcher, a total of ۱۰۰ classes and subclasses, ۱۹ object properties, ۹ data properties, and ۱۱۴ instances were identified. Subsequently, the cognitive warfare ontology model was designed using Protégé software, and its RDF representation was developed. In the next phase, the cognitive warfare knowledge graph was constructed using GraphDB software, based on the RDF file generated by Protégé, and its visualization was performed using Gephi software. The findings of the research demonstrated that utilizing AI technologies and tools such as GraphDB and Gephi optimizes the process of ontology design and knowledge graph creation in the domain of cognitive warfare. The cognitive warfare knowledge graph, through its semantic structure representation, enables a more precise description of concepts, semantic representation of relationships among them, and a deeper understanding of the semantic relationships in this domain. Moreover, leveraging the graphical features and visualization of the cognitive warfare knowledge graph plays a significant role in rendering the complex communication network comprehensible, as well as identifying and analyzing hidden patterns and relationships among data in this domain.

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نویسندگان

Akram Fathian Dastgerdi

Assistant Prof., Knowledge and Information Science, Islamic World Science & Technology Monitoring and Citation Institute, Shiraz, Iran