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. |
From inside the book
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... example, in medical decisions, data mining can produce a pattern that can be used to predict the effect of possible treatments. Adding this information to the information pool will allow better decisions than when only the observations ...
... example non numeric, highly unbalanced, unclean data) as well as with non-structured data (for example text, images, multimedia, and event data). Finally, while one of the main goals of statistics is hypothesis testing, one of the main ...
... example, that available in database systems. There are initiatives in this direction, which will diminish the monopoly of expensive closed-architecture systems. For data mining to be truly successful it is important for it to become ...
... examples. 3.1. Induction. of. models. for. classification. and. prediction. In a classification task, data is usually formed from examples (records of given attribute values) which are labeled by the class to which they belong. The task at ...
... example rule-set in the form of a decision list – a set of if-then rules interpreted sequentially in the if-then-else fashion – describing if a person in Slovenia reads the daily newspaper EN (Evening News, a newspaper published in ...
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 |