options have been taken into consideration. By using a clustering algorithm for analyzing both the database containing events …

incorporate data dependency in the clustering process. In this research we focus on clustering categorical sequences. The method … proposed here combines model-based and heuristic clustering. In the first step, the categorical sequences are transformed by an …, in the second step, using hierarchical clustering on the matrix of distances, the sequences can be clustered. This paper …

, keyword extraction, dimensionality reduction and clustering using the diffusion map algorithm is presented. We use publicly …

time as the most effective fraud detection method in 2011. Out of the available data mining techniques, clustering has … proven itself a constant applied solution for detecting fraud. This paper surveys clustering techniques used in fraud …

This paper review some state-of-the art non-parallel and parallel approaches of data clustering and present the … usefulness of parallel genetic algorithms (PGAs) for clustering. In solving the clustering problem many traditional methods stuck … general it is unknown to the user. Therefore, clustering becomes a trial-and-error work and is also very expensive in terms of …