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A Survey on Knowledge Graph Structure and Knowledge Graph Embeddings
Knowledge Graphs (KGs) and their machine learning counterpart, Knowledge Graph Embedding Models (KGEMs), have seen ever-increasing use in a wide variety of academic and applied settings. In particular, KGEMs are typically applied to KGs to solve the link prediction task; i.e. to predict new facts in the domain of a KG based on existing, observed facts.
Sardina, Jeffrey +2 more
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, 2020 Knowledge graphs are increasingly built using complex multifaceted machine learning-based systems relying on a wide of different data sources. To be effective these must constantly evolve and thus be maintained. Here work is presented on combining knowledge graph construction (e.g. information extraction) and refinement (e.g. link prediction) in end to
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Wikidata and the biodiversity knowledge graph [PDF]
Biodiversity Information Science and Standards, 2019 This talk explores the role Wikidata (Vrandečić and Krötzsch 2014) might play in the task of assembling biodiversity information into a single, richly annotated and cross linked structure known as the biodiversity knowledge graph (Page 2016). Initially conceived as a language-independent data store of facts derived from the Wikipedia, Wikidata has ...
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Advanced Biology, EarlyView.Chromatin, which organizes DNA, changes its structure to adapt to stress like high oxygen levels (hyperoxia), which can damage cells. Researchers developed a technique to observe these changes and found variability in how different parts of chromatin remodel.
Lauren Monroe +4 more
wiley +1 more source
Adopting Graph Traversal Techniques for Context-Driven Value Sets Extraction from Biomedical Knowledge Sources [PDF]
, 2008 Jyotishman Pathak +4 more
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Advanced Biology, EarlyView.The axolotl's remarkable regenerative abilities decline with age, the causes may include the numerous repetitive elements within its genome. This study uncovers how Ty3 retrotransposons and coexpression networks involving muscle and immune pathways respond to aging and regeneration, suggesting that transposons respond to physiological shifts and may ...
Samuel Ruiz‐Pérez +8 more
wiley +1 more source
Finding compound structures in images using image segmentation and graph-based knowledge discovery [PDF]
, 2009 Daniya Zamalieva +2 more
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Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Advanced Engineering Materials, EarlyView.Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Temporal power modulation increases weld depth in high‐power laser beam welding of dissimilar round bars by nearly 20% compared to same average continuously welded welding power. The mechanism of action also applies to sheet welding and depends on the inertia of keyhole depth for the modulated laser beam power.
Jan Grajczak +7 more
wiley +1 more source
Knowledge Graphs 2023 - 6.1 The Graph in Knowledge Graphs
, 2023 Sack, Harald, Tan, Mary Ann
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