Results 21 to 30 of about 290,132 (291)
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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Knowledge Graph Embeddings [PDF]
, 2012 With the growing popularity of multi-relational data on the Web, knowledge graphs (KGs) have become a key data source in various application domains, such as Web search, question answering, and natural language understanding. In a typical KG such as Freebase (Bollacker et al.
Rosso, Paolo +2 more
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Journal of Big Data, 2023 The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions.
Bilal Abu-Salih +5 more
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, 2023 <p>This survey discusses the concept of knowledge graphs, including their construction, extraction, and applications. Various tools such as Zotero, Web of Science, Google Scholar, EndNote, and VosViewer are used to analyze and visualize collected data. A Boolean query mechanism ensures the gathered material is relevant to the study.
Abiola Akinnubi, Jeremiah Ajiboye
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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, Juan F. Sequeda
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Survey on Inductive Learning for Knowledge Graph Completion [PDF]
Jisuanji kexue yu tansuo, 2023 Knowledge graph completion can make knowledge graph more complete. However, traditional knowledge graph completion methods assume that all test entities and relations appear in the training process.
LIANG Xinyu, SI Guannan, LI Jianxin, TIAN Pengxin, AN Zhaoliang, ZHOU Fengyu
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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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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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Building a PubMed knowledge graph [PDF]
Scientific Data, 2020 AbstractPubMed® is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguous, which has significantly hindered knowledge discovery. To address this issue, we constructed a PubMed knowledge graph (PKG) by extracting bio-entities from 29 million PubMed abstracts, disambiguating author names ...
Xu, Jian +14 more
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Translational Oncology, 2021 Objectives: The subtype classification of lung adenocarcinoma is important for treatment decision. This study aimed to investigate the deep learning and radiomics networks for predicting histologic subtype classification and survival of lung ...
Chengdi Wang +9 more
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