Data Mining and Decision Support: Integration and CollaborationDunja Mladenic, Nada Lavrač, Marko Bohanec, Steve Moyle Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting. |
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Marko Bohanec (marko.bohanec (G)ijs.si) is a senior researcher at Jožef Stefan Institute, Department of Intelligent Systems, Ljubljana, and assistant professor in information systems at the University of Ljubljana, School of Public ...
Bojan Cestnik (bojan.cestnik Qtemida.si) is the general manager of the software company Temida and a researcher at the Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana, Slovenia. His professional and research ...
Branko Kavšek (branko.kavsek Qijs.si) is a member of the Intelligent Data Analysis and Computational Linguistics Research Group at Jožef Stefan Institute, Ljubljana, Slovenia. His research covers machine learning, inductive databases, ...
Nada Lavrač (nada.lavrac®ijs.si) is Head of the Intelligent Data Analysis and Computational Linguistics Research Group at Jožef Stefan Institute, Ljubljana, Slovenia. Her research interests include machine learning, relational data ...
He is also a research fellow at the Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana, Slovenia. His research focuses on information systems and artificial intelligence methods for supporting decision and educational ...
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Contents
1 | |
TEXT AND WEB MINING | 15 |
DECISION SUPPORT | 23 |
INTEGRATION OF DATA MINING AND DECISION | 37 |
COLLABORATION IN A DATA MINING VIRTUAL | 49 |
DATA MINING PROCESSES AND COLLABORATION | 63 |
AN INTRODUCTION | 80 |
SUPPORTING | 91 |
MINING 21 YEARS OF | 142 |
ANALYSIS OF A DATABASE OF RESEARCH PROJECTS | 157 |
WEBSITE ACCESS ANALYSIS FOR A NATIONAL | 167 |
FIVE DECISION SUPPORT APPLICATIONS | 177 |
COLLABORATIVE DATA MINING WITH RAMSYS | 215 |
LESSONS LEARNED FROM DATA MINING DECISION | 237 |
A KNOWLEDGE | 247 |
ACADEMIABUSINESS PARTNERSHIP MODELS | 261 |
PREPROCESSING FOR DATA MINING AND DECISION | 107 |
DATA MINING AND DECISION SUPPORT INTEGRATION | 118 |
APPLICATIONS OF DATA MINING | 131 |
Subject index 271 | 270 |