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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... clusters, and other patterns that can be of interest to the user. Data mining has recently gained much attention from industry, due to the existence of large collections of data in different formats, and the increasing need for data ...
... clustering — and searching for patterns and models of interest. 5. Evaluation and interpretation of results: aided by visualization, transformation, and removing redundant patterns. 6. Deployment; the use of the discovered knowledge. A ...
... clustering, while subgroup discovery — aimed at finding descriptions of interesting population subgroups — is a form of supervised learning. 3.2.1 Association rule induction The task of discovering association rules has received much ...
... Clustering Clustering is an unsupervised learning method (Hartigan, 1975), meaning that training examples are not labeled by their class membership. The goal of clustering is to partition a set of data into groups, called clusters, such ...
... clustering. This section briefly describes three data mining applications, whose full descriptions can be found in Chapters 11, 12 and 8, respectively. 4.1. The. analysis. of. media. surveys. Consider the problem of analyzing questionnaires ...
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 |