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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... decision tree learning techniques, which are mostly concerned with the discovery of classificatory properties of data tables. Data represented in tables may be collected typically from measurements or acquired from clients. Rows in the ...
... decision tree induction (Quinlan, 1986), such as C4.5, generate a decision tree from a given set of attribute-value tuples. The tree are heuristically guided by choosing the “most informative' attribute at each node, aimed at minimizing ...
... decision tree, modeling the profile of readers of a teenage magazine. The induced set of rules can be used for classification. A rule set is usually interpreted in a top-down manner as if-then-else rules (a decision list) and the first ...
... decision tree and a set of rules represent a model that can be used for classification and/or prediction, the goal of data analysis may be different. Instead of model construction, the goals may be the discovery of individual patterns ...
... tree or dendrogram. A sample dendrogram is shown in Figure 1-2. A dendrogram is a tree where the initial clusters, consisting of one element only, form the leaves of the tree. Each internal node represents a cluster that is formed by ...
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 |