Download Data mining and knowledge discovery in databases have been attr

INDUSTRIAL ENGINEERING AND SYSTEMS MANAGEMENT
CONFERENCE 2007
May 30 – June 2, 2007, Beijing, China
Special track on Healthcare Management and Engineering
Call for papers - Special Session on
Data Mining and Knowledge Discovery in Databases applied to
healthcare systems delivery
http://www.i4e2.com/iesm/
Session chairs: Catherine COMBES and François Jacquenet – Hubert Curien Laboratory - UMR
CNRS 5516 – University Jean Monnet of Saint-Etienne – France.
Session description
Knowledge Discovery in Databases (KDD) combines Data Warehousing/Databases and
techniques from data mining, machine learning, pattern recognition, statistics… to automatically
extract concepts and their interrelations and patterns of interest from large databases.
Data Mining and Knowledge Discovery in Databases (KDD) have been attracting and the
capabilities offered by KDD are becoming extremely important today relating to the amounts of
the data collected in various fields and more particularly in healthcare systems delivery.
It is increasingly important to develop software tools to assist in the extraction of information and
knowledge from data, understanding the implications of data in databases, and automatic
construction of knowledge bases from databases.
Contributions emphasizing recent advances and new research directions are strongly encouraged.
Submissions describing real case studies in healthcare domain is recommended.
Recommended topics
Researchers and practitioners are invited to submit complete original papers dealing to healthcare
domain with the following topics but are not limited to:
- Data warehousing,
- Data collection and preparation,
- Data visualization techniques,
- Data cleaning, dimension reduction, discretization…,
- Data mining techniques,
- Pre-processing and post-processing for data mining,
- Robust and scalable statistical methods,
- KDD framework and process,
- Database interfaces for efficient mining and visualization,
- Symbolic data analysis,
- Statistical approaches used in machine learning,
- Representing, modeling, and reasoning.
The application only concerns healthcare systems delivery.
Instructions to authors
Authors are requested to provide a full paper of 10 pages maximum, written in English, according to
the instructions: www.i4e2.com/iesm-policy.
Express your intention of submission and send an abstract to introduce the topics of your article to
[email protected].
Draft papers should be submitted by November 30, 2006
Authors will receive the acceptance notification by January 15, 2007
Final papers for presentation should be sent before February 15, 2007