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In this paper, we propose a pre-processing technique to improve existing string similarity join algorithms using fuzzy clustering. Our approach first identifies groups of related attributes and then, using this information, we apply existing string similarity join algorithms on these attributes. To identify the clustered attributes we use fuzzy techniques. This approach can be applied to the integration...
String is a primary data format in majority of applications. With the rapid growth of diverse data driven applications in the current information era, retrieving string data from heterogeneous structured sources becomes more and more significant and challenging. The main concern is duplicate records are created when data is integrated from heterogeneous sources. Those duplicate records represent the...
Mining biclusters that exhibit both consistent trends and trends with similar degrees of fluctuations is vital to bioinformatics research. However; existing biclustering methods are not very efficient and effective at mining such biclusters. Moreover, few inter-bicluster relationships are delivered to biologists. In this paper, we introduce a quick hierarchical biclustering algorithm (QHB) to efficiently...
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