Name
Abstract | ||
|---|---|---|
AbstractOrder-preserving submatrices OPSMs find objects that exhibit a coherent pattern with the same linear ordering in subspace. In general, this problem can be reducible to a special case of the sequential pattern mining problem, where a pattern and its supporting sequences uniquely specify an OPSM. In this paper, we extend the idea of order-preserving submatrix and define a new model semi-order-preserving submatrix or SOPSM that can be generalised to cover most existing bicluster models, and then propose a novel exact algorithm for mining all significant SOPSMs. To reduce the computational costs, we further propose a pruning technique and design an improved data structure for prefix tree to speed up the running time of the algorithm. A set of extensive experiments have been performed which demonstrate the effectiveness and efficiency of our method in mining SOPSMs. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1504/IJCSE.2016.077734 | Periodicals |
Keywords | Field | DocType |
data mining, bicluster, order-preserving submatrix, OPSM | Computer science,A priori and a posteriori,Theoretical computer science,Artificial intelligence,Biclustering,Trie,Speedup,Data structure,Exact algorithm,Subspace topology,Algorithm,Block matrix,Machine learning | Journal |
Volume | Issue | ISSN |
13 | 1 | 1742-7185 |
Citations | PageRank | References |
2 | 0.37 | 11 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun Xue | 1 | 11 | 3.59 |
| TieChen Li | 2 | 8 | 3.57 |
| Haolan Zhang | 3 | 12 | 5.09 |
| Xiaosheng Wu | 4 | 54 | 7.48 |
| Meihang Li | 5 | 8 | 3.83 |
| Xiao-Hui Hu | 6 | 10 | 5.55 |