A generic and extendible Multi-Agent Data Mining (MADM) framework, EMADS (the Extendible Multi-Agent Data mining System) is described. The central feature of the framework is that it avoids the use of agreed meta-language formats by supporting a system of wrappers. The advantage offered is that the system is easily extendible, so that further data agents and mining agents can simply be added to...

Data warehouse (DW) is a repository with query interface in support of Decision support systems. DW required answering many complex queries, managerial level queries and analytical queries, needing to develop advanced computing techniques. The DW system process involving data modeling, ETL process, query interface and reporting system. Materialized views (MV) are the pre calculated views which ...

1 HFAR Hospital das Foras Armadas, Azinhaga Ulmeiros, 1620-060 Lisboa, Portugal [email protected] 2 ALGORITMI Research Centre, Department of Information Systems, University of Minho, 4800-058 Guimarães, Portugal [email protected] WWW home page: http://www3.dsi.uminho.pt/pcortez 3 Business Research Unit (UNIDE-IUL), Instituto Universitário de Lisboa (ISCTE-IUL), Av. das Forças Armadas, 162...

Data warehouse (DW) is a repository with query interface in support of Decision support systems. DW required answering many complex queries, managerial level queries and analytical queries, needing to develop advanced computing techniques. The DW system process involving data modeling, ETL process, query interface and reporting system. Materialized views (MV) are the pre calculated views which ...

I will describe a novel meta-learning approach to optimizing the knowledge discovery or data mining (DM) process. This approach has three features that distinguish it from its predecessors. First, previous meta-learning research has focused exclusively on improving the learning phase of the DM process. More specifically, the goal of meta-learning has typically been to select the most appropriat...

This paper presents basic ideas and results of the GOAL project focusing on its knowledge discovery part. Within this project a KDD (Knowledge Discovery in Databases) package [7] has been designed and implemented. In this paper motivation, architecture, functionality and one two of the implemented DM (data mining) modules of the KDD Package are described in greater detail. KDD Package supports ...

A data mining (DM) process involves multiple stages. A simple, but typical, process might include preprocessing data, applying a data-mining algorithm, and postprocessing the mining results. There are many possible choices for each stage, and only some combinations are valid. Because of the large space and non-trivial interactions, both novices and data-mining specialists need assistance in com...

The rate at which organizations are acquiring data is exploding and managing such data so as to infer useful knowledge that can be put to use is increasingly becoming important. Data Mining (DM) is one such technology that is employed in inferring useful knowledge that can be put to use from a vast amount of data. This paper presents the data mining activity that was employed in weather data pr...

OBJECTIVE Data Mining is a relatively new field of Medical Informatics. The aim of this study was to compare Data Mining diagnosis with clinical diagnosis by applying a Data Miner (DM) to a clinical dataset of infertile men with azoospermia. DESIGN One hundred and forty-seven azoospermic men were clinically classified into four groups: a) obstructive azoospermia (n=63), b) non-obstructive azo...

In the last few decades, Grid technologies have emerged as an important area in parallel and distributed computing. The Grid can be seen as a computational and large-scale support, and even in some cases as a high-performance support. In recent years, the data mining community have been increasingly using Grid facilities to store, share, manage and mine large-scale data-driven applications. Ind...