Zobrazeno 1 - 10
of 920
pro vyhledávání: '"knowledge graph completion"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Drug repurposing aims to find new therapeutic applications for existing drugs in the pharmaceutical market, leading to significant savings in time and cost. The use of artificial intelligence and knowledge graphs to propose repurposing candi
Externí odkaz:
https://doaj.org/article/214bcb1e00c6445daeae7c62296c2045
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 3, Pp 646-658 (2024)
Most few-shot knowledge graph completion models have some problems, such as low ability to learn relation representation and rarely attaching importance to the relative location and interaction between query entity pair when the relation between enti
Externí odkaz:
https://doaj.org/article/0787fb83a8334e3389ea740bdf7a3d9f
Publikováno v:
IEEE Access, Vol 12, Pp 179566-179578 (2024)
Knowledge graphs (KGs) possess a vital role in enhancing the semantic comprehension of extensive datasets across many fields. It facilitate activities like recommendation systems, semantic searching, and intelligent data mining. However, lacking info
Externí odkaz:
https://doaj.org/article/c29c595d222d4d4ba37f6a3a9be85392
Publikováno v:
IEEE Access, Vol 12, Pp 177012-177027 (2024)
The completeness of knowledge graphs is critical to their effectiveness across various applications. However, existing knowledge graph completion methods face challenges such as difficulty in adapting to new entity information, parameter explosion, a
Externí odkaz:
https://doaj.org/article/5d6649fbaaf0418d826ac73e45f81bbd
Publikováno v:
IEEE Access, Vol 12, Pp 173338-173350 (2024)
Knowledge graph embedding maps the semantics of entities and relations to a low-dimensional space by optimizing the vector distance between positive and negative triples. Traditional negative sampling techniques usually regard high-scoring triples as
Externí odkaz:
https://doaj.org/article/c7a501961b2f47c8a1814301fad2403f
Autor:
Muhammad Yahya, Abdul Wahid, Lan Yang, John G. Breslin, Evgeny Kharlamov, Muhammad Intizar Ali
Publikováno v:
IEEE Access, Vol 12, Pp 89804-89817 (2024)
The integration of heterogeneous and unstructured data in Industry 4.0, poses a significant challenge, particularly with advanced manufacturing techniques. To address this issue, Knowledge Graphs (KGs) have emerged as a pivotal technology, yet their
Externí odkaz:
https://doaj.org/article/469d838adf0d450699a0683b53cd9e91
Autor:
Hong Zheng, Shanqin Li
Publikováno v:
IEEE Access, Vol 12, Pp 78101-78109 (2024)
In this study, we primarily address the issue of uneven quality of client embeddings in existing federated learning frameworks for knowledge graph completion. Although existing frameworks provide preliminary solutions to the heterogeneity of data in
Externí odkaz:
https://doaj.org/article/b5c8b2911f0c44168db4efcd16efaf30
Publikováno v:
IEEE Access, Vol 12, Pp 57250-57260 (2024)
This paper presents Integrated Semantics-Structure Analysis in Knowledge Graph Completion (ISA-KGC), a new framework for Knowledge Graph Completion (KGC) aimed at addressing the incompleteness of knowledge graphs (KGs). ISA-KGC integrates Graph Neura
Externí odkaz:
https://doaj.org/article/fe97650c8d7641e48cd7e528e8473c63
Publikováno v:
IEEE Access, Vol 12, Pp 40973-40988 (2024)
Recently, Dynamic knowledge graphs (DKGs) have been considered the foundation stone for several powerful knowledge-aware applications. DKG has a great advancement over static knowledge graph with the ability to capture the dynamicity of knowledge. Th
Externí odkaz:
https://doaj.org/article/430a7d26d02b4e5781c302f930c7da8d
Autor:
Yang Liu, Tianran Tao, Xuemei Liu, Jiayun Tian, Zehong Ren, Yize Wang, Xingzhi Wang, Ying Gao
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 1, Pp 1394-1412 (2024)
In response to the limited capability of extracting semantic information in knowledge graph completion methods, we propose a model that combines spatial transformation and attention mechanisms (STAM) for knowledge graph embedding. Firstly, spatial tr
Externí odkaz:
https://doaj.org/article/fc01c3fe94084743b7af5a5c9af05ec9