نوع مقاله : مقاله مروری
نویسندگان
دانشکده برق و کامپیوتر، دانشگاه کاشان، کاشان، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Knowledge graphs are essential and widely used tools in data mining, machine learning, complex networks, and related fields. They represent important entities as nodes and their relationships as edges. In this paper, we conduct a comprehensive review of these graphs and their related methods. We focus on RGNN networks, TDM, and BLM methods, and evaluate their performance and results in depth. This study provides a thorough analysis of the advantages and disadvantages of these methods in dealing with real-world problems and applications. We also present tests on two graphs of biology and general knowledge.
کلیدواژهها [English]