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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
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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
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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
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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
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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
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Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 2020 Knowledge Graphs can be considered as fulfilling an early vision in Computer Science of creating intelligent systems that integrate knowledge and data at large scale. Stemming from scientific advancements in research areas of Semantic Web, Databases, Knowledge representation, NLP, Machine Learning, among others, Knowledge Graphs have rapidly gained ...
Claudio Gutierrez 0001, Juan F. Sequeda
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Narrativizing Knowledge Graphs
, 2022 Any natural language expression of a set of facts – that can be represented as a knowledge graph – will more or less overtly assume a specific perspective on these facts. In this paper we see the conversion of a given knowledge graph into natural language as the construction of a narrative about the assertions made by the knowledge graph. We, therefore,
Porzel, Robert +5 more
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ACM SIGMOD Record, 2023 Knowledge graphs (KGs) such as DBpedia, Freebase, YAGO, Wikidata, and NELL were constructed to store large-scale, real-world facts as (subject, predicate, object) triples - that can also be modeled as a graph, where a node (a subject or an object) represents an entity with attributes, and a directed edge (a predicate) is a relationship between two ...
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CoRR, 2020 Knowledge graphs (KGs) have shown to be an important asset of large companies like Google and Microsoft. KGs play an important role in providing structured and semantically rich information, making them available to people and machines, and supplying accurate, correct and reliable knowledge.
Elwin Huaman +2 more
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