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pro vyhledávání: '"He D"'
Publikováno v:
Scopus-Elsevier
The objective of discovering network communities, an essential step in complex systems analysis, is two-fold: identification of functional modules and their semantics at the same time. However, most existing community-finding methods have focused on
Publikováno v:
Scopus-Elsevier
Detection of overlapping communities has drawn much attention lately as they are essential properties of real complex networks. Despite its influence and popularity, the well studied and widely adopted stochastic model has not been made effective for
Publikováno v:
Scopus-Elsevier
An important problem in analyzing complex networks is discovery of modular or community structures embedded in the networks. Although being promising for identifying network communities, the popular stochastic models often do not preserve node degree
Publikováno v:
Genetics and molecular research : GMR. 13(1)
This study aimed to investigate the function and signaling pathway of Toll-like receptor 4 (TLR4) in oxidized low-density lipoprotein (oxLDL)-induced up-regulated expressions of oxidized LDL receptor 1 (LOX-1), monocyte chemoattractant protein 1 (MCP
Publikováno v:
Scopus-Elsevier
Community detection has been extensively studied for various applications, focusing primarily on network topologies. Recent research has started to explore node contents to identify semantically meaningful communities and interpret their structures u
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04cae690a159467922226eb21997d82a
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http://www.scopus.com/inward/record.url?eid=2-s2.0-85052215344&partnerID=MN8TOARS
Publikováno v:
Scopus-Elsevier
Discovery of communities in networks is a fundamental data analysis problem. Most of the existing approaches have focused on discovering communities of nodes, while recent studies have shown great advantages and utilities of the knowledge of communit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9750236c7970a833484462db60dc6fd4
http://www.scopus.com/inward/record.url?eid=2-s2.0-84959477859&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84959477859&partnerID=MN8TOARS
Publikováno v:
Scopus-Elsevier
Markov Random Field (MRF) is a powerful framework for developing probabilistic models of complex problems. MRF models possess rich structures to represent properties and constraints of a problem. It has been successful on many application problems, p
Externí odkaz:
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http://www.scopus.com/inward/record.url?eid=2-s2.0-85060442269&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85060442269&partnerID=MN8TOARS