Results 51 to 60 of about 7,092,434 (358)

Survey on Inductive Learning for Knowledge Graph Completion [PDF]

open access: yesJisuanji 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
doaj   +1 more source

Building a knowledge graph to enable precision medicine

open access: yesbioRxiv, 2022
Measurement(s) knowledge graph • Relation Code • textual entity Technology Type(s) machine learning • computational modeling technique Developing personalized diagnostic strategies and targeted treatments requires a deep understanding of disease biology ...
P. Chandak, Kexin Huang, M. Zitnik
semanticscholar   +1 more source

Deep Bidirectional Language-Knowledge Graph Pretraining [PDF]

open access: yesNeural Information Processing Systems, 2022
Pretraining a language model (LM) on text has been shown to help various downstream NLP tasks. Recent works show that a knowledge graph (KG) can complement text data, offering structured background knowledge that provides a useful scaffold for reasoning.
Michihiro Yasunaga   +6 more
semanticscholar   +1 more source

Knowledge Graph: A Survey

open access: yes, 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
openaire   +1 more source

Knowledge Questions from Knowledge Graphs [PDF]

open access: yesProceedings 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.
openaire   +3 more sources

Building a PubMed knowledge graph [PDF]

open access: yesScientific 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
openaire   +5 more sources

Deep learning for predicting subtype classification and survival of lung adenocarcinoma on computed tomography

open access: yesTranslational 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
doaj  

RAGAT: Relation Aware Graph Attention Network for Knowledge Graph Completion

open access: yesIEEE Access, 2021
Knowledge graph completion (KGC) is the task of predicting missing links based on known triples for knowledge graphs. Several recent works suggest that Graph Neural Networks (GNN) that exploit graph structures achieve promising performance on KGC.
Xiyang Liu   +3 more
doaj   +1 more source

Low-Dimensional Hyperbolic Knowledge Graph Embeddings [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2020
Knowledge graph (KG) embeddings learn low- dimensional representations of entities and relations to predict missing facts. KGs often exhibit hierarchical and logical patterns which must be preserved in the embedding space.
Ines Chami   +5 more
semanticscholar   +1 more source

Knowledge Graphs of Kawasaki Disease [PDF]

open access: yesHealth Information Science and Systems, 2021
AbstractKawasaki Disease is a vasculitis syndrome that is extremely harmful to children. Kawasaki Disease can cause severe symptoms of ischemic heart disease or develop into ischemic heart disease, leading to death in children. Researchers and clinicians need to analyze various knowledge and data resources to explore aspects of Kawasaki Disease ...
Guanghua Liu   +7 more
openaire   +3 more sources

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