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Constrained Dual Graph Regularized Orthogonal Nonnegative Matrix Tri-Factorization for Co-Clustering
Joint Authors
Li, Hongjun
Ge, Shaodi
Luo, Liuhong
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-26
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Coclustering approaches for grouping data points and features have recently been receiving extensive attention.
In this paper, we propose a constrained dual graph regularized orthogonal nonnegative matrix trifactorization (CDONMTF) algorithm to solve the coclustering problems.
The new method improves the clustering performance obviously by employing hard constraints to retain the priori label information of samples, establishing two nearest neighbor graphs to encode the geometric structure of data manifold and feature manifold, and combining with biorthogonal constraints as well.
In addition, we have also derived the iterative optimization scheme of CDONMTF and proved its convergence.
Clustering experiments on 5 UCI machine-learning data sets and 7 image benchmark data sets show that the achievement of the proposed algorithm is superior to that of some existing clustering algorithms.
American Psychological Association (APA)
Ge, Shaodi& Li, Hongjun& Luo, Liuhong. 2019. Constrained Dual Graph Regularized Orthogonal Nonnegative Matrix Tri-Factorization for Co-Clustering. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1197092
Modern Language Association (MLA)
Ge, Shaodi…[et al.]. Constrained Dual Graph Regularized Orthogonal Nonnegative Matrix Tri-Factorization for Co-Clustering. Mathematical Problems in Engineering No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1197092
American Medical Association (AMA)
Ge, Shaodi& Li, Hongjun& Luo, Liuhong. Constrained Dual Graph Regularized Orthogonal Nonnegative Matrix Tri-Factorization for Co-Clustering. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1197092
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197092