Grouping customer transactions into segments is important in order to obtain better understanding of customers’ pattern. Currently, the hierarchical pattern-based clustering has been used to group customer transactions into segments. However, the processing time is still high due to difference parameter used between two clusters. In this paper, the difference will be based on the different betw...

Protein-Protein Interaction (PPI) networks contain valuable information for the isolation of groups of proteins that participate in the same biological function. Many proteins play different roles in the cell by taking part to several processes, but isolating the different processes in which a protein is involved is often a difficult task. In this paper we present a method based on a greedy loc...

A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calculations to parallel computers. The method employs a combination of iterative techniques to both evenly balance theworkload andminimise the number and volume of interprocessor communications. They are designed to work efficiently in parallel as well as sequentially and when combined with a fast dir...

In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In a data stream processing, memory usage is restricted, new elements are generated continuously and have to be considered as fast as possible, no blocking operator can be performed and the data can be examined only once. At this time ...

The density-based clustering algorithm presented is different from the classical Density-Based Spatial Clustering of Applications with Noise (DBSCAN) (Ester et al., 1996), and has the following advantages: first, Greedy algorithm substitutes for R(*)-tree (Bechmann et al., 1990) in DBSCAN to index the clustering space so that the clustering time cost is decreased to great extent and I/O memory ...

Motivated by problems in video summarization caused by change in lighting, we develop a new low-dimensional feature video frame feature that is more insensitive to such changes than previous methods. Because we effectively reduce any video to the same lighting conditions, we can produce a universal basis on which to project video frame features. We set out a new multi-stage hierarchical cluster...

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Feature Selection (FS) is applied to reduce the number of features in many applications where data has multiple features. FS is an essential step in successful data mining applications, which can effectively reduce data dimensionality by removing t...

This paper introduces a new hybrid algorithmic nature inspired approach based on the concepts of the Honey Bees Mating Optimization Algorithm (HBMO) and of the Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm for the Clustering Analysis, the Hybrid HBMO-GRASP, is a two phase algorithm which combines a HBMO algorithm ...

Oligonucleotide fingerprinting is a powerful DNA array based method to characterize cDNA and ribosomal RNA gene (rDNA) libraries and has many applications including gene expression profiling and DNA clone classification. We are especially interested in the latter application. A key step in the method is the cluster analysis of fingerprint data obtained from DNA array hybridization experiments. ...

Wireless sensor networks(WSNs) consists of a large number of wireless sensor nodes that have sensing, data processing and communication functionalities. WNSs are typically used to monitor a field of interest to detect movement, temperature changes, precipitation etc. Energy Consumption and Coverage are two major problems in wireless sensor networks. We implement our proposed scheme in NS-2 as a...