April 16, 2024, 4:44 a.m. | Zhiwei Hu, V\'ictor Guti\'errez-Basulto, Zhiliang Xiang, Ru Li, Jeff Z. Pan

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.09848v1 Announce Type: cross
Abstract: In a hyper-relational knowledge graph (HKG), each fact is composed of a main triple associated with attribute-value qualifiers, which express additional factual knowledge. The hyper-relational knowledge graph completion (HKGC) task aims at inferring plausible missing links in a HKG. Most existing approaches to HKGC focus on enhancing the communication between qualifier pairs and main triples, while overlooking two important properties that emerge from the monotonicity of the hyper-relational graphs representation regime. Stage Reasoning allows for …

abstract arxiv cs.ai cs.lg express focus graph knowledge knowledge graph relational representation type value

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

#13721 - Data Engineer - AI Model Testing

@ Qualitest | Miami, Florida, United States

Elasticsearch Administrator

@ ManTech | 201BF - Customer Site, Chantilly, VA