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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... solution is even in space and it stays at any time in the ball of center 0 and radius Cε of = η0 ,ψ| t=0 = ψ0 (T1,R). H s+ 1 40 (T1,R) × ̇Hs−1 4 The above theorem establishes almost global existence of solutions to the capillarygravity ...
... Solutions . All solutions were prepared from analytical grade chemicals and laboratory distilled water . The stock solutions , and , in many cases , the actual dilutions used , were analyzed for their cation concentration by appropriate ...
... solutions of 0.2 normal amyl amine and acetic acid the color changes from pink to light orange . The results varied about 2 per cent . In the kerosene solutions , two or three drops of the saturated solution of the indicator in ethyl ...
... solutions to any significant extent . The difference between the results shown in figure 3 and those from the previous experiment given in figure 2 suggests that oxidation of the manganese was a more important factor in solutions 13-18 ...
... solutions turn litmus paper blue , therefore it is basic . Ethyl methyl amine is in solubility class Sg . j . propoxybenzene -OCH2CH2CH3 Propoxybenzene is insoluble in water because it has more than five carbon atoms . It is a neutral ...
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 |