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
Results 1-5 of 42
Data mining is concerned with solving problems by analyzing existing data. ... of these two technologies has a significant impact on the developments of both fields, largely by improving approaches for problem solving in real settings, ...
Part IV presents practical advantages and limitations of collaborative problem solving framework in a virtual enterprise formed from remote teams collaborating mostly via the Internet. The first two chapters of this part report on ...
The ultimate purpose of industrial data mining is the use of the resulting patterns to solve some problem: ... A complementary approach to such problem solving that does not rely on collecting observational data is decision making.
... have recognised the need for methods and tools that include a larger part of the problem solving process than data analysis. A methodology that covers the process from problem definition to presentation and delivery of the resulting ...
The solutions are applied to public participation processes, cooperative spatial planning projects and sustainable communication processes for decision-making, problem solving and knowledge sharing.
What people are saying - Write a review
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 |