Greedy Modifications of OAC-triclustering Algorithm

In this paper we propose several possible modifications to the OAC-triclustering algorithms based on the prime operators. This method based on the framework of Formal Concept Analysis showed some rather promising results in the previous research. But while it is fast and efficient with respect to such measures as average density of the output, diversity, coverage, and noise- tolerance, it produces rather large number of triclusters. This makes it almost impossible for the expert to manually check the results. We show that the proposed post-processing techniques not only reduce the size of the output for this approach and keep the good values for the measures, but also keep the time complexity of the original algorithm