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. |
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... , text and Web mining techniques and their applications, especially learning from large text data sets. He has worked on several national and international projects in text and data mining, Internet xviii Data mining and decision support.
... datasets in a very efficient way, while the algorithmic complexity of statistical methods may turn out to be prohibitive for their use on very large databases. Next, the results of the analysis need to be represented in an appropriate ...
... dataset in terms of a fixed collection of attributes (properties), as is the case with transactional databases. More sophisticated tools are needed for data mining from relational databases and data warehouses. Methods and tools for the ...
... dataset analysis (see Chapter 11), a task of this type was defined by the following question: “Which other journals/magazines do readers of a particular journal/magazine read?” As opposed to decision tree and rule set induction, such a ...
... dataset was relatively large (1.5GB) and multi-relational, and the data mining task was exploratory mining rather than simple prediction. As analyzing road safety data is a highly exploratory process, it critically depends on asking 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 |