نوع مقاله : مقاله پژوهشی
نویسنده
گروه اشاعه اطلاعات و دانش، پژوهشکده مدیریت اطلاعات و مدارک اسلامی، پژوهشگاه علوم و فرهنگ اسلامی، قم، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسنده [English]
The emergence and maturation of artificial intelligence technologies, particularly the Semantic Web, knowledge graphs, and large language models, have opened new horizons in this domain. This paper presents an analytical and critical review of the convergence of these three technological streams in Islamic text knowledge management systems over the period 2023 to 2026. The primary objective is not only to identify and categorize recent advancements but also to provide an in-depth engineering assessment of them from the perspectives of system architecture, scalability, semantic accuracy, reliability, and domain-specific compliance. Through a rigorous analysis of the research literature (over seventy selected articles from an initial pool of two hundred titles), a novel conceptual framework is proposed for analyzing intelligent Islamic text knowledge management systems, encompassing technical dimensions, methodological aspects, and domain considerations. The findings reveal that while technologies such as semantic knowledge graphs and large language models have demonstrated remarkable capabilities in organizing, retrieving, and generating knowledge from Islamic texts, fundamental challenges remain as major obstacles to achieving fully trustworthy and high-performance systems. These include the phenomenon of hallucination in language models, the siloed nature of ontologies, the scarcity of high-quality annotated datasets, the complexities of chain-of-transmission authentication, and the need for model interpretability. The paper concludes by presenting a six-axis research roadmap, illuminating future directions for the development of intelligent Islamic text knowledge management systems that can effectively and responsibly address the needs of Islamic text analysis and processing.
کلیدواژهها [English]
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