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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PART II INTEGRATION ASPECTS OF DATA MINING 10. AND DECISION SUPPORT 79 Edited by Marko Bohanec DECISION SUPPORT FOR DATA MINING: AN INTRODUCTION TO ROC ANALYSIS AND ITS APPLICATIONS 81 Peter Flach, Hendrik Blockeel, Cèsar Ferri, ...
Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and ...
Several practice-oriented research efforts in data mining have recognised the need for methods and tools that include a larger part of the problem solving process than data analysis. A methodology that covers the process from problem ...
His research interests include machine learning, knowledge discovery, and intelligent data analysis. He has worked on various induction-based data analysis applications in medical and marketing domains, and has set up the Internet Data ...
He has organized several international conferences and other events in artificial intelligence and data mining. He is the coordinator of the data analysis and decision support systems masters program at the University of Porto, ...
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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 |