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 34
... association and classification rules, and Web mining. He has organized several international conferences and other ... Society. Martin Kejkula (kejkula @vse.cz) is a member of the Laboratory for Intelligent systems (LISp) in Prague ...
... rule discovery and business problems. Olga. Štěpánková. (stepGlabefelk.cvut.cz). is. Vice-head. of. the. Department. of. Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, and president of the Czech ...
... guidelines are very useful both for the data analyst and the client. The individual steps of the CRISP-DM process are ... association, clustering — and searching for patterns and models of interest. 5. Evaluation and interpretation 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 ... association rule learning and classification rule learning can be used to solve 10 Chapter 1.
... rule learning can be used to solve the subgroup discovery task, as in the case of propositional algorithms SD (Gamberger ... association rules for subgroup discovery, confirmed that such an accident frequently occurred on UK roads in the ...
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 |