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Most of the existing algorithms for mining frequent items on data stream do not emphasis the importance of the recent data items. We present an algorithm to detect the items with frequency counts exceeding a user-specified threshold. Our algorithm uses a hash table L and a heap to record the potential frequent items, and can detect ??-approximate frequent data items on data stream using O(|L|+ ??-1...
Biclustering the gene expressing data is an important task in bioinformatics. A parallel biclustering algorithm for gene expressing data is presented. The algorithm starts from the data sets containing pair of rows and columns of the data matrix, and gets the biclusters by gradually adding columns and rows on the data sets. A pruning technique is also proposed to reduce computing time. Experimental...
A biclustering algorithm for gene expressing data is presented. Based on the anti-monotones property of the quality of the data sets with their sizes, the algorithm can get the final biclusters by gradually adding columns and rows on the data sets. Experimental results show that our algorithm has higher processing speed and quality of clustering than other similar algorithms.
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