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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... Section 2 provides the background to data mining , Section 3 describes in a simplified manner - some data mining techniques that proved to be useful in the development of applications described in this book . Selected data mining ...
... section , we cite ( Friedman , 1997 ) stating why data mining holds the intellectual , academic and commercial future : " Every time the amount of data increases by a factor of ten , we should totally rethink how we analyze it . " 2.2 ...
... they belong . Supervised learning assumes that training examples are classified whereas unsupervised learning concerns the analysis of unclassified examples . In the following sections we outline some data mining tasks Data mining 7.
... sections we outline some data mining tasks , discuss the appropriate methods for solving the tasks and illustrate the results of applying these methods through examples . 3.1 Induction of models for classification and prediction In a ...
... methods . Among these , the K - Means method is one of the most popular . This method was applied in an application described in Chapter 11 . 4 . SELECTED DATA MINING APPLICATIONS This section briefly describes Data mining 11.
Contents
| 3 | |
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 |
WEB SITE 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 |
Other editions - View all
Data Mining and Decision Support: Integration and Collaboration Dunja Mladenic,Nada Lavrač,Marko Bohanec,Steve Moyle No preview available - 2012 |