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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... Hendrik Blockeel, Cčsar Ferri, José Hernández-Orallo, and Jan Struyf DATA MINING FOR DECISION SUPPORT: SUPPORTING MARKETING DECISIONS THROUGH SUBGROUP DISCOVERY 91 Bojan Cestnik, Nada Lavrač, Peter Flach, Dragan Gamberger, ...
The second chapter addresses the complementary data mining for decision support approach, illustrated by two methods applied in marketing. The final two chapters of Part II describe the integration of data mining and decision support in ...
In practice data mining is becoming an established technology with applications in a wide range of areas that include marketing, health care, finance, environment, economic planning, career planning, and military.
He has worked on various induction-based data analysis applications in medical and marketing domains, and has set up the Internet Data Mining Server. Thomas Gärtner (thomas.gaertner (G)ais.fraunhofer.de) is a PhD candidate at the ...
Mihael Kline (kline-kline G\siol.net) is assistant professor of consumer psychology, integrated marketing communications and basics of visual communication at the Faculty of social sciences of the University of Ljubljana, Slovenia.
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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 |