Results 11 to 20 of about 353,050 (214)
ACM Computing Surveys, 2021 In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data.
Aidan Hogan +17 more
+23 more sources
Knowledge graph embeddings: open challenges and opportunities [PDF]
, 2023 While Knowledge Graphs (KGs) have long been used as valuable sources of structured knowledge, in recent years, KG embeddings have become a popular way of deriving numeric vector representations from them, for instance, to support knowledge graph ...
Russa Biswas +9 more
core +2 more sources
Wikibase as an Infrastructure for Knowledge Graphs: The EU Knowledge Graph [PDF]
, 2021 Knowledge graphs are being deployed in many enterprises and institutions. An easy-to-use, well-designed infrastructure for such knowledge graphs is not obvious. After the success of Wikidata, many institutions are looking at the software infrastructure behind it, namely Wikibase.
Dennis Diefenbach +2 more
openaire +2 more sources
XR4DRAMA Knowledge Graph: A Knowledge Graph for Disaster Management
2023 IEEE 17th International Conference on Semantic Computing (ICSC), 2023 The evolution of Knowledge Graphs (KGs), during the last two decades, has encouraged developers to create more and more context related KGs. This advance is extremely important because Artificial Intelligence (AI) applications can access open domain specific information in a semantically rich, machine understandable format.
Alexandros Vassiliades +6 more
openaire +1 more source
XR4DRAMA Knowledge Graph: A Knowledge Graph for Media Planning
Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023 In the previous two decades, knowledge graphs have evolved, inspiring developers to build even more context related Knowledge Graphs. Because of this development, artificial intelligence applications can now access open domain-specific information in a format that is both semantically rich and machine comprehensible.
Alexandros Vassiliades +5 more
openaire +2 more sources
A type-augmented knowledge graph embedding framework for knowledge graph completion
Scientific Reports, 2023 Knowledge graphs (KGs) are of great importance to many artificial intelligence applications, but they usually suffer from the incomplete problem.
Peng He +4 more
doaj +1 more source
Text-Graph Enhanced Knowledge Graph Representation Learning
Frontiers in Artificial Intelligence, 2021 Knowledge Graphs (KGs) such as Freebase and YAGO have been widely adopted in a variety of NLP tasks. Representation learning of Knowledge Graphs (KGs) aims to map entities and relationships into a continuous low-dimensional vector space.
Linmei Hu +6 more
doaj +1 more source
IEEE Access, 2022 In recent years, although the application of knowledge graph in natural language processing has made some progress, there are still some key problems to be solved, especially the matching query problem in natural language knowledge graph. Since the basic
Qifeng Zou, Chaoze Lu
doaj +1 more source
Survey on Visualization Query Technology of Knowledge Graph [PDF]
Jisuanji gongcheng, 2020 Knowledge graph,as the development product of symbolism,is considered to be an important part of artificial intelligence technologies and systems,and widely used in encyclopedia knowledge,biological information,social network,network security and so on ...
WANG Xin, FU Qiang, WANG Lin, XU Dawei, WANG Haofen
doaj +1 more source
A Knowledge Graph Perspective on Knowledge Engineering
SN Computer Science, 2022 AbstractFor over 50 years researchers and practitioners have searched for ways to elicit and formalize expert knowledge to support AI applications. Expert systems and knowledge bases were all results of these efforts. The initial efforts on knowledge bases were focused on defining a domain and task intensionally with rather complex ontologies.
Simsek, Umutcan +7 more
openaire +1 more source