Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximating Maximum Clique by Removing Subgraphs
SIAM Journal on Discrete Mathematics
Minimum Spanning Tree Partitioning Algorithm for Microaggregation
IEEE Transactions on Knowledge and Data Engineering
Minimum Spanning Tree Based Clustering Algorithms
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Multi-objective evolutionary biclustering of gene expression data
Pattern Recognition
A clustering algorithm based on maximal θ-distant subtrees
Pattern Recognition
Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
IEEE Transactions on Computers
Overlapping Community Detection in Bipartite Networks
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Extraction and classification of dense implicit communities in the Web graph
ACM Transactions on the Web (TWEB)
A Divide-and-Conquer Approach for Minimum Spanning Tree-Based Clustering
IEEE Transactions on Knowledge and Data Engineering
Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting Multi-facet Community Structure from Bipartite Networks
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data clustering: 50 years beyond K-means
Pattern Recognition Letters
Inapproximability of maximum weighted edge biclique and its applications
TAMC'08 Proceedings of the 5th international conference on Theory and applications of models of computation
Dividing protein interaction networks for modular network comparative analysis
Pattern Recognition Letters
Supervised Machine Learning Applied to Link Prediction in Bipartite Social Networks
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Dense subgraph problems with output-density conditions
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Hybrid minimal spanning tree and mixture of gaussians based clustering algorithm
FoIKS'06 Proceedings of the 4th international conference on Foundations of Information and Knowledge Systems
An exact exponential time algorithm for counting bipartite cliques
Information Processing Letters
Smooth Chan-Vese segmentation via graph cuts
Pattern Recognition Letters
Computer Science Review
A mixed graph model for community detection
International Journal of Intelligent Information and Database Systems
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In this paper we introduce a graph clustering method based on dense bipartite subgraph mining. The method applies a mixed graph model (both standard and bipartite) in a three-phase algorithm. First a seed mining method is applied to find seeds of clusters, the second phase consists of refining the seeds, and in the third phase vertices outside the seeds are clustered. The method is able to detect overlapping clusters, can handle outliers and applicable without restrictions on the degrees of vertices or the size of the clusters. The running time of the method is polynomial. A theoretical result is introduced on density bounds of bipartite subgraphs with size and local density conditions. Test results on artificial datasets and social interaction graphs are also presented.