Results 51 to 60 of about 247,759 (306)
Measuring Accuracy of Triples in Knowledge Graphs [PDF]
, 2017 An increasing amount of large-scale knowledge graphs have been constructed in recent years. Those graphs are often created from text-based extraction, which could be very noisy. So far, cleaning knowledge graphs are often carried out by human experts and
Shuangyan Liu +6 more
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Restricting the Spurious Growth of Knowledge Graphs by Using Ontology Graphs
IEEE AccessKnowledge Graphs have demonstrated a real advantage in knowledge representation, leveraging graphs NoSQL structures and schema-less technology, which offers superior comprehension, knowledge representation, interpretation, and reasoning.
Kina Tatchukova, Yanzhen Qu
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Collective knowledge graph: meta knowledge transfer and federated graph reasoning
智能科学与技术学报, 2022 Collective knowledge graphs refer to knowledge graphs that are managed and maintained in a decentralized or distributed manner through group collaboration.Compared with the existing centrally managed knowledge graph, the collective knowledge graph has ...
Mingyang CHEN +4 more
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Learning Typed Rules over Knowledge Graphs
, 2022 Rule learning from large datasets has regained extensive interest as rules are useful for developing explainable approaches to many applications in knowledge graphs.
Wang, Z +7 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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An Embedding-based Approach to Rule Learning in Knowledge Graphs
, 2019 It is natural and effective to use rules for representing explicit knowledge in knowledge graphs. However, it is challenging to learn rules automatically from very large knowledge graphs such as Freebase and YAGO.
Wang, Z, Wang, K, Ghiasnezhad Omran, P
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Enhancing Biomedical Knowledge Representation Through Knowledge Graphs
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceThere is a plethora of information related to the biomedical domain on the internet. Unfortunately, retrieving this information online is challenging because of insufficient semantic metadata embedded within the web documents that help search engines ...
Sebastian Chalarca +4 more
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Knowledge Graphs and Explainable AI in Healthcare
Information, 2022 Building trust and transparency in healthcare can be achieved using eXplainable Artificial Intelligence (XAI), as it facilitates the decision-making process for healthcare professionals.
Enayat Rajabi, Somayeh Kafaie
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K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain
IEEE Access, 2022 The use of superior algorithms and complex architectures in language models have successfully imparted human-like abilities to machines for specific tasks.
Vivek Kumar +3 more
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Knowledge Questions from Knowledge Graphs [PDF]
Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval, 2017 We address the novel problem of automatically generating quiz-style knowledge questions from a knowledge graph such as DBpedia. Questions of this kind have ample applications, for instance, to educate users about or to evaluate their knowledge in a specific domain. To solve the problem, we propose an end-to-end approach.
Seyler, D., Yahya, M., Berberich, K.
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