This paper presents a distributed architecture for automating data mining processes using standard languages. Data mining is a difficult task that relies on an exploratory and analytic process of processing large quantities of data in order to discover meaningful patterns. The increasing heterogeneity and complexity of available data requires some expert knowledge on how to combine the multiple...

This research report is written for attendance of DMC 2002. (See [8]) It was written following the CRISP-DM (CRISPData Mining) [1] Methodology: Business understanding, Data Understanding, Data Preparation, Modeling and Evaluation. Two popular data mining software products are used: DISCOVERER is mainly used for data preparation and modeling. WEKA is used to feature selection. At the last part o...

Applying Kansei Engineering in fabric design requires the establishment of a common research platform in a design respect of view that involves both subjects. This platform can help designers investigate the methods to increase the added value of fabrics, and provides theories, techniques, and basis for designing. Kansei, which used to be considered as qualitative, immeasurable, irrational, and...

The constant increase in use of geographic data in different application domains has resulted in large amounts of data stored in spatial databases and in the desire of data mining. Many solutions for spatial data mining have been proposed. Most create data mining languages or extend existing query languages to support data mining operations. This paper presents an interoperable framework for sp...

The global aim of Kansei design studies is to bring Kansei related aspects to design methods and means, ultimately targeting the improvement of design outputs. The motivation of such target is to improve the relationship between an individual (the user) and her/his environment (whether it is physical or social one). This can be done by understanding and evaluating better designers and users’ Ka...

This paper presents a tool for web usage mining. The aim is centered on providing a tool that facilitates the mining process rather than implement elaborated algorithms and techniques. The tool covers different phases of the CRISP-DM methodology as data preparation, data selection, modeling and evaluation. The algorithms used in the modeling phase are those implemented in the Weka project. The ...

Data mining is a process of extracting knowledge from underlying huge multidimensional data. Data mining techniques discovers hidden patterns from a given data. Classification is one of the techniques of data mining. Data Classification consists of categorization of data under the known class labels for its most effective and efficient utilization. There are different algorithms available for c...

This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple data set, then proceeds to explain how one might approach a bioinformatics problem. Finally, it includes a brief summary of machine learning algorith...