Results 41 to 50 of about 48,760 (297)
Time-Aware Probabilistic Knowledge Graphs [PDF]
, 2019 The emergence of open information extraction as a tool for constructing and expanding knowledge graphs has aided the growth of temporal data, for instance, YAGO, NELL and Wikidata.
Chekol, Melisachew Wudage +1 more
core +1 more source
TeCoRe: temporal conflict resolution in knowledge graphs [PDF]
, 2017 The management of uncertainty is crucial when harvesting structured content from unstructured and noisy sources. Knowledge Graphs (kgs), maintaining both numerical and non-numerical facts supported by an underlying schema, are a prominent example ...
Chekol, Melisachew Wudage +11 more
core +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Selective Temporal Knowledge Graph Reasoning
Proceedings of the Language Resources and Evaluation ConferenceTemporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently. TKG reasoning aims to predict future facts based on given historical ones. However, existing TKG reasoning models are unable to abstain from predictions they are uncertain, which ...
Zhongni Hou +5 more
openaire +3 more sources
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks [PDF]
, 2021 Large knowledge graphs often grow to store temporal facts that model the dynamic relations or interactions of entities along the timeline. Since such temporal knowledge graphs often suffer from incompleteness, it is important to develop time-aware ...
Fan, Changjun +4 more
core +1 more source
One-shot Learning for Temporal Knowledge Graphs
CoRR, 2020 Most real-world knowledge graphs are characterized by a long-tail relation frequency distribution where a significant fraction of relations occurs only a handful of times. This observation has given rise to recent interest in low-shot learning methods that are able to generalize from only a few examples.
Mehrnoosh Mirtaheri +4 more
openaire +2 more sources
FEBS Open Bio, EarlyView.Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
Temporal Representation in Semantic Graphs [PDF]
, 2007 A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts.
Levandoski, J J, Abdulla, G M
core +1 more source
Data extraction table for a systematic review on modelling temporal data in knowledge graphs [PDF]
, 2021 A Data extraction table including the headings only to structure and categorise the findings of a systematic review on temporal data modelling in knowledge ...
Fabrizio Orlandi (11349946) +5 more
core +1 more source