Two-dimensional data partitioning for non-negative matrix tri-factorization

As a two-sided clustering and dimensionality reduction paradigm, Non-negative Matrix Tri-Factorization (NMTF) has attracted much attention in machine learning and data mining researchers due to its excellent performance and reliable theoretical support. Unlike Non-negative Matrix Factorization (NMF)...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Big data research Jg. 37; S. 100473
Hauptverfasser:	Yan, Jiaxing, Liu, Hai, Lei, Zhiqi, Rao, Yanghui, Liu, Guan, Xie, Haoran, Tao, Xiaohui, Wang, Fu Lee
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 28.08.2024
Schlagworte:	2-Dimensional data partitioning Non-negative matrix tri-factorization Text co-clustering 2-Dimensional data partitioning Text co-clustering Non-negative matrix tri-factorization
ISSN:	2214-5796, 2214-580X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!