activity
20192022
most citedHyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion

20 citations · 33 across the 5 of their papers we have counts for

collaborators

6 papers

cs.SE2022★ 1 cited

Ontology-based system to support industrial system design for aircraft assembly

Xiaodu Hu, Rebeca Arista, Xiaochen Zheng +5

The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces…

cs.AI2021

Actionable Cognitive Twins for Decision Making in Manufacturing

Jože M. Rožanec, Jinzhi Lu, Jan Rupnik +5

Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive capabilities through a knowledge graph and artificial intelligence models that provide insi…

cs.SE2020★ 2 cited

Design Ontology Supporting Model-based Systems-engineering Formalisms

Lu Jinzhi, Ma Junda, Xiaochen Zheng +2

Model-based systems engineering (MBSE) provides an important capability for managing the complexities of system development. MBSE empowers the formalisms of system architectures fo…

eess.SY2020★ 3 cited

Towards a Decentralized Digital Engineering Assets Marketplace: Empowered by Model-based Systems Engineering and Distributed Ledger Technology

Jinzhi Lu, Xiaochen Zheng, Zhenchao Hu +2

Model-based Systems Engineering (MBSE) has been widely utilized to formalize system artifacts and facilitate their development throughout the entire lifecycle. During complex syste…

eess.SY2020★ 7 cited

Cognitive Twins for Supporting Decision-Makings of Internet of Things Systems

Jinzhi Lu, Xiaochen Zheng, Ali Gharaei +2

Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of…

cs.CL2019★ 20 cited

HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion

Prodromos Kolyvakis, Alexandros Kalousis, Dimitris Kiritsis

Learning embeddings of entities and relations existing in knowledge bases allows the discovery of hidden patterns in data. In this work, we examine the geometrical space's contribu…