A comprehensive overview of knowledge graph completion
T Shen, F Zhang, J Cheng - Knowledge-Based Systems, 2022 - Elsevier
Abstract Knowledge Graph (KG) provides high-quality structured knowledge for various
downstream knowledge-aware tasks (such as recommendation and intelligent question …
downstream knowledge-aware tasks (such as recommendation and intelligent question …
[HTML][HTML] CAFE: Knowledge graph completion using neighborhood-aware features
Abstract Knowledge Graphs (KGs) currently contain a vast amount of structured information
in the form of entities and relations. Because KGs are often constructed automatically by …
in the form of entities and relations. Because KGs are often constructed automatically by …
Rule mining over knowledge graphs via reinforcement learning
Abstract Knowledge graphs (KGs) are an important source repository for a wide range of
applications and rule mining from KGs recently attracts wide research interest in the KG …
applications and rule mining from KGs recently attracts wide research interest in the KG …
Towards semantically enhanced digital twins
E Kharlamov, F Martin-Recuerda… - … Conference on Big …, 2018 - ieeexplore.ieee.org
Digital twins (DTs) are a powerful mechanism for representing complex industrial assets
such as oil platforms as digital models. These models can facilitate temporal analyses and …
such as oil platforms as digital models. These models can facilitate temporal analyses and …
Adversarial learning for debiasing knowledge graph embeddings
Knowledge Graphs (KG) are gaining increasing attention in both academia and industry.
Despite their diverse benefits, recent research have identified social and cultural biases …
Despite their diverse benefits, recent research have identified social and cultural biases …
Towards generalized welding ontology in line with ISO and knowledge graph construction
Towards Generalized Welding Ontology in Line with ISO and Knowledge Graph Construction |
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Generating rules to filter candidate triples for their correctness checking by knowledge graph completion techniques
Knowledge Graphs (KGs) contain large amounts of structured information. Due to their
inherent incompleteness, a process known as KG completion is often carried out to find the …
inherent incompleteness, a process known as KG completion is often carried out to find the …
An ontology-mediated analytics-aware approach to support monitoring and diagnostics of static and streaming data
Streaming analytics that requires integration and aggregation of heterogeneous and
distributed streaming and static data is a typical task in many industrial scenarios including …
distributed streaming and static data is a typical task in many industrial scenarios including …
Information extraction from document images via fca-based template detection and knowledge graph rule induction
We view information extraction from document images as a complex problem that requires a
combination of 1) state of the art deep learning vision models for detection of entities and …
combination of 1) state of the art deep learning vision models for detection of entities and …
Too much information: Can AI cope with modern knowledge graphs?
M Krötzsch - … Analysis: 15th International Conference, ICFCA 2019 …, 2019 - Springer
Abstract Knowledge graphs play an important role in artificial intelligence (AI) applications–
especially in personal assistants, question answering, and semantic search–and public …
especially in personal assistants, question answering, and semantic search–and public …