Journal: Intelligent Data Analysis
Special Issue: Business Analytics and Intelligent Optimization

During the last decades, the disciplines of Data Mining and Operations Research have been working mostly independent of each other. The increasing complexity of today’s applications in areas such as business, medicine, and science requires, however, more and more interaction between both disciplines. On the one hand, many data mining algorithms rely on optimization methods, and incorporating state-of-the-art optimization techniques may improve the efficiency and effectiveness of data mining algorithms. On the other hand, there are many optimization problems that would benefit from an integration of data mining and knowledge discovery processes (KDD). Furthermore, the combined use of both disciplines would provide superior solutions in many application domains, particularly in an attempt to take into account the entire decision making process.

This special issue will help address the needs for a well balanced methodological development in order to document the state-of-the-art of this emerging area, as well as present experiences generated by successful applications.

We are inviting researchers to submit top-quality papers indicating clearly their contribution to one of the following areas:

• Optimization Methods in the process of Knowledge Discovery,
• Data Mining in Operations Research,
• Application/case study papers focused on Business Analytics and Intelligent Optimization.

Interesting issues that could be addressed are e.g.:

• How can optimization techniques be used to improve the steps of the KDD process, such as sampling, feature selection, feature extraction, visualization, classification, clustering, among others?
• How can data mining help to enhance optimization tasks, using e.g. the different aspects of pattern recognition as preprocessing for large-scale optimization models?
• Application papers from any area such marketing, finance, operations, medicine, social sciences, among others are welcome. It should be indicated clearly, however, which particular advantage the combined use of data mining and optimization provides.


Deadlines:
Paper submission deadline:
October 15, 2010

Accept/revise/reject decisions:
March 15, 2011

Revised final manuscript due date:
April 30, 2011


Submission:
The submissions are to be sent electronically to both Guest Editors (pdf files). The manuscripts should adhere to the formal guidelines of the journal, see: http://www.iospress.nl/loadtop/load.php?isbn=1088467x

Guest Editors:
Prof. Dr. Kate Smith-Miles
School of Mathematical Sciences,
Faculty of Science, Monash University, Australia.
kate.smith-miles@sci.monash.edu.au

Prof. Dr. Richard Weber
Department of Industrial Engineering
Universidad de Chile
rweber@dii.uchile.cl