Md Anisur Rahman

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In this paper we present a novel clustering technique called Seed-Detective. It is a combination of modified versions of two existing techniques namely Ex-Detective and Simple K-Means. Seed-Detective first discovers a set of preliminary clusters using our modified Ex-Detective. The modified Ex-Detective allows a data miner to assign different weights(More)
We present a novel fuzzy clustering technique called CRUDAW that allows a data miner to assign weights on the attributes of a data set based on their importance (to the data miner) for clustering. The technique uses a novel approach to select initial seeds deterministically (not randomly) using the density of the records of a data set. CRUDAW also selects(More)
The task of combining data residing at different sources to provide the user a unified view is known as data integration. Schema mappings act as glue between the global schema and the source schemas of a data integration system. Global-and-local-as-view (GLAV) is one the approaches for specifying the schema mappings. Tableaux are used for expressing queries(More)
Many existing clustering techniques including K-Means require a user input on the number of clusters. It is often extremely difficult for a user to accurately estimate the number of clusters in a data set. The genetic algorithms (GAs) generally determine the number of clusters automatically. However, they typically choose the genes and the number of genes(More)
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