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Efficient High-Quality Clustering for Large Bipartite Graphs
Renchi Yang
, Jieming Shi
*
*
Corresponding author for this work
Department of Computer Science
Research output
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Journal article
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peer-review
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Dive into the research topics of 'Efficient High-Quality Clustering for Large Bipartite Graphs'. Together they form a unique fingerprint.
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Keyphrases
Bipartite Graph
100%
Graph Clustering
58%
High Efficiency
16%
Vertex Set
16%
Disjoint
16%
High-order
16%
Social Network Analysis
8%
Order of Magnitude
8%
Bioinformatics
8%
Clustering Problem
8%
Low-rank Approximation
8%
Cluster Solutions
8%
Clustering Accuracy
8%
Cluster Performance
8%
Clustering Results
8%
Text Mining
8%
Frobenius Norm
8%
Optimization Framework
8%
Cluster Quality
8%
High Clustering
8%
User-item
8%
Biological Interactions
8%
Art Performance
8%
High Scalability
8%
Problem Formulation
8%
Recommendation System
8%
High-order Information
8%
Spectral Norm
8%
Two-stage Optimization
8%
Problem Transformation
8%
Target Vertices
8%
Computer Science
Clustering Quality
100%
Bipartite Graph
100%
Order Perspective
16%
Large Data Set
8%
Text Mining
8%
Social Network Analysis
8%
Bioinformatics
8%
Clustering Result
8%
High Clustering
8%
Order Information
8%
Optimization Framework
8%
Rank Approximation
8%
Art Performance
8%
Problem Formulation
8%
Article Publication
8%