document: Carpenter : finding closed patterns in long biological datasets The growth of bioinformatics has resulted in datasets with new characteristics . These datasets typically contain a large number of columns and a small number of rows . For example , many gene expression datasets may contain 10,000-100 ,000 columns but only 100-1000 rows . Such datasets pose a great challenge for existing ( closed ) frequent pattern discovery algorithms , since they have an exponential dependence on the average row length . In this paper , we describe a new algorithm called CARPENTER that is specially designed to handle datasets having a large number of attributes and relatively small number of rows . Several experiments on real bioinformatics datasets show that CARPENTER is orders of magnitude better than previous closed pattern mining algorithms like CLOSET and CHARM .
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