Name
Title | ||
|---|---|---|
Bipartite Edge Correlation Clustering: Finding An Edge Biclique Partition From A Bipartite Graph With Minimum Disagreement |
Abstract | ||
|---|---|---|
In this paper, first we formulate the problem of a bipartite edge correlation clustering which finds an edge biclique partition with the minimum disagreement from a bipartite graph, by extending the bipartite correlation clustering which finds a biclique partition. Then, we design a simple randomized algorithm for bipartite edge correlation clustering, based on the randomized algorithm of bipartite correlation clustering. Finally, we give experimental results to evaluate the algorithms from both artificial data and real data. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.5220/0007471506990706 | ICPRAM: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS |
Keywords | Field | DocType |
Bipartite Edge Correlation Clustering, Edge Biclique Partition, Minimum Disagreement, Bipartite Correlation Clustering, Bicluster Graph Editing, Biclustering | Randomized algorithm,Complete bipartite graph,Combinatorics,Correlation clustering,Pattern recognition,Computer science,Bipartite graph,Artificial intelligence,Biclustering,Partition (number theory) | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mikio Mizukami | 1 | 0 | 0.34 |
| Kouichi Hirata | 2 | 130 | 32.04 |
| Tetsuji Kuboyama | 3 | 140 | 29.36 |