Clustering is a division of data into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar compared to objects of other groups. This paper is intended to study and compare different data clustering algorithms. The algorithms under investigation are: k-means algorithm, hierarchical clustering algorithm, self-organizing ma...

The purpose of BARCODE HOUSING SYTEM, a research project developed over the last four years, has been to create an Internet-based system which facilitates the interaction of the different actors involved in the design, construction and use of affordable housing built with industrialized methods. One of the components of the system is an environment which enables different users – architects, cl...

Unrepresentative data samples are likely to reduce the utility of data classifiers in practical application. This study presents a hybrid mining approach in the design of an effective credit scoring model, based on clustering and neural network techniques. We used clustering techniques to preprocess the input samples with the objective of indicating unrepresentative samples into isolated and in...

This paper introduces a set of algorithmic modifications that improve the partitioning results obtained with ant-based clustering. Moreover, general parameter settings and a self-adaptation scheme are devised, which afford the algorithm’s robust performance across varying data sets. We study the sensitivity of the resulting algorithm with respect to two distinct, and generally important, featur...

Marketing segmentation is widely used for targeting a smaller market and is useful for decision makers to reach all customers effectively with one basic marketing mix. Although several clustering algorithms have been proposed to deal with marketing segmentation problems, a soundly method seems to be limited. In this paper, support vector clustering (SVC) is used for marketing segmentation. A ca...

background: the population of elderly in iran and in the world is increasing. it is predicted that the population of elderly reaches to 10 millions in iran by the year 2019. elderly more than other age groups are at risk of chronic diseases and health problems; and it affects their self-management and makes them feel disabled. since the knowledge of self-management for iranian elderly is not we...

According to the problem of K value and initial cluster centers selection difficult on K-means clustering algorithm, form essential characteristics of the complex network, the fault samples can be abstracted into network nodes, and the connection between samples can be abstracted into edge, and then the network model of fault data can be established .Failure data network model is divided into s...

We present a novel approach to the clustering of gene expression patterns based on the mutual connectivity of the patterns. Unlike certain widely used methods (e.g., self-organizing maps and K-means) which essentially force gene expression data into a xed number of predetermined clustering structures, our approach aims to reveal the natural tendency of the data to cluster, in analogy to the phy...