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 ...
... 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 ...
... be found in Chapter 11 . 4.2 The analysis of UK traffic accident data The UK. Figure 1-2 . A dendrogram , constructed through hierarchical clustering . Figure 3-1 . The position of decision support within the. 12 Chapter 1.
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 |