Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information ne...

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Detalles Bibliográficos
Autores principales: Wu, Jibing, Meng, Qinggang, Deng, Su, Huang, Hongbin, Wu, Yahui, Badii, Atta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330508/
https://www.ncbi.nlm.nih.gov/pubmed/28245222
http://dx.doi.org/10.1371/journal.pone.0172323

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330508/
https://www.ncbi.nlm.nih.gov/pubmed/28245222
http://dx.doi.org/10.1371/journal.pone.0172323

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