## 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 67

...

**Section**2 provides the background to data mining ,

**Section**3 describes in a simplified manner - some data mining techniques that proved to be useful in the development of applications described in this book . Selected data mining ...

...

**section**, we cite ( Friedman , 1997 ) stating why data mining holds the intellectual , academic and commercial future : " Every time the amount of data increases by a factor of ten , we should totally rethink how we analyze it . " 2.2 ...

... they belong . Supervised learning assumes that training examples are classified whereas unsupervised learning concerns the analysis of unclassified examples . In the following

**sections**we outline some data mining tasks Data mining 7.

...

**sections**we outline some data mining tasks , discuss the appropriate methods for solving the tasks and illustrate the results of applying these methods through examples . 3.1 Induction of models for classification and prediction In a ...

... methods . Among these , the K - Means method is one of the most popular . This method was applied in an application described in Chapter 11 . 4 . SELECTED DATA MINING APPLICATIONS This

**section**briefly describes Data mining 11.

### 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 |