Data Mining and Decision Support: Integration and Collaboration / Edition 1
  • Data Mining and Decision Support: Integration and Collaboration / Edition 1
  • Data Mining and Decision Support: Integration and Collaboration / Edition 1

Data Mining and Decision Support: Integration and Collaboration / Edition 1

by Dunja Mladenic
     
 

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. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data

See more details below

Overview

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. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses. 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.

Read More

Product Details

ISBN-13:
9781402073885
Publisher:
Springer US
Publication date:
09/30/2003
Series:
The Springer International Series in Engineering and Computer Science, #745
Edition description:
2003
Pages:
275
Product dimensions:
0.75(w) x 6.14(h) x 9.21(d)

Table of Contents

Preface
Acknowledgments
Foreword
Contributing Authors
Pt. IBasic Technologies1
1Data Mining3
2Text and Web Mining15
3Decision Support23
4Integration of Data Mining and Decision Support37
5Collaboration in a Data Mining Virtual Organization49
6Data Mining Processes and Collaboration Principles63
Pt. IIIntegration Aspects of Data Mining and Decision Support79
7Decision Support for Data Mining: An introduction to ROC analysis and its applications81
8Data Mining for Decision Support: Supporting marketing decisions through subgroup discovery91
9Preprocessing for Data Mining and Decision Support107
10Data Mining and Decision Support Integration through the Predictive Model Markup Language Standard and Visualization119
Pt. IIIApplications of Data Mining and Decision Support131
11Analysis of Slovenian Media Space133
12On the Road to Knowledge: Mining 21 years of UK traffic accident reports
13Analysis of a Database of Research Projects Using Text Mining and Link Analysis157
14Web Site Access Analysis for a National Statistical Agency167
15Five Decision Support Applications177
16Large and Tall Buildings: A case study in the application of decision support and data mining191
17A Combined Data Mining and Decision Support Approach to Educational Planning203
Pt. IVCollaboration Aspects213
18Collaborative Data Mining with Ramsys and Sumatra TT: Prediction of resources for a health farm215
19Collaborative Decision Making: An environmental case study227
20Lessons Learned from Data Mining, Decision Support and Collaboration237
21Internet Support to Collaboration: A knowledge management and organizational memory view247
22Mind the Gap: Academia-business partnership models and e-collaboration lessons learned261
Subject index271

Read More

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >