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Cybersecurity knowledge graphs
Knowledge and Information Systems, 2023 AbstractCybersecurity knowledge graphs, which represent cyber-knowledge with a graph-based data model, provide holistic approaches for processing massive volumes of complex cybersecurity data derived from diverse sources. They can assist security analysts to obtain cyberthreat intelligence, achieve a high level of cyber-situational awareness, discover ...
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Advances in Knowledge Graph Embedding Based on Graph Neural Networks [PDF]
Jisuanji kexue yu tansuo, 2023 As graph neural networks continue to develop, knowledge graph embedding methods based on graph neural networks are receiving increasing attention from researchers.
YAN Zhaoyao, DING Cangfeng, MA Lerong, CAO Lu, YOU Hao
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Considering semantics on the discovery of relations in knowledge graphs
, 2022 S.666-680Knowledge graphs encode semantic knowledge that can be exploited to enhance different data-driven tasks, e.g., query answering, data mining, ranking or recommendation.
Vidal, Maria-Esther +3 more
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LifeGraph: A Knowledge Graph for Lifelogs [PDF]
Proceedings of the Third Annual Workshop on Lifelog Search Challenge, 2020 The data produced by efforts such as life logging is commonly multi modal and can have manifold interrelations with itself as well as external information. Representing this data in such a way that these rich relations as well as all the different sources can be leveraged is a non-trivial undertaking.
Rossetto, Luca +5 more
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BioMedInformatics, 2023 Semantic web technologies (SWT) represent data in a format that is easier for machines to understand. Validating the knowledge in data graphs created using SWT is critical to ensure that the axioms accurately represent the so-called “real” world. However,
Rashmi Burse +2 more
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Integration of OPC UA information models into Enterprise Knowledge Graphs
, 2022 Building repositories of data relevant for enterprise operations requires harmonization of formats and semantics. OPC UA’s nodes-and-references data model shares basic elements with well-established semantic modeling technologies like RDF.
Arno Weiss +3 more
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Frontiers in Big Data, 2021 Knowledge graphs are a modern way to store information. However, the knowledge they contain is not static. Instances of various classes may be added or deleted and the semantic relationship between elements might evolve as well.
Jon Haël Brenas, Arash Shaban-Nejad
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williamjsdavis/Knowledge-Graphs-for-Seismic-Data-and-Metadata: Update from reviewer comments
, 2023 <p>Minor naming changes following with reviewer comments in the associated paper "Knowledge Graphs for Seismic Data and Metadata" (<a href="https://doi.org/10.31223/X5XQ1D">DOI:10.31223/X5XQ1D</a>) by William Davis and ...
William Davis
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Rule Learning over Knowledge Graphs: A Review [PDF]
, 2023 Compared to black-box neural networks, logic rules express explicit knowledge, can provide human-understandable explanations for reasoning processes, and have found their wide application in knowledge graphs and other downstream tasks.
Wang, Zhe +4 more
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Keyphrase Extraction Using Knowledge Graphs
Data Science and Engineering, 2017 Extracting keyphrases from documents automatically is an important and interesting task since keyphrases provide a quick summarization for documents. Although lots of efforts have been made on keyphrase extraction, most of the existing methods (the co ...
Wei Shi +4 more
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