An effective algorithm for mining 3-clusters in vertically partitioned data
Proceedings of the 17th ACM conference on Information and knowledge management
Algorithm for low-variance biclusters to identify coregulation modules in sequencing datasets
Proceedings of the Tenth International Workshop on Data Mining in Bioinformatics
Mining low-variance biclusters to discover coregulation modules in sequencing datasets
Scientific Programming - Biological Knowledge Discovery and Data Mining
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We present a search algorithm for mining closed sets in high dimensional binary datasets. Our algorithm is designed for dense datasets, where the percentage of 1's in the dataset is usually higher than 10%, and the total number of closed sets is much larger than the number of objects in the dataset. Our algorithm is memory efficient since, unlike many other closed set mining algorithms, it does not require all patterns mined so far to be kept in the memory. Optimization techniques are introduced in this paper, and we also present a parallel version of our algorithm.