IDA-2001 will take place in Lisbon from 13th to 15th September 2001, and is organised by the Department of Computer Science of the Faculty of Science and Technology of the New University of Lisbon. It will consist of a stimulating program of invited talks by leading international experts in intelligent data analysis, contributed papers, poster sessions, and an exciting social program.
Our aim is for IDA-2001 to bring together a wide variety of researchers concerned with extracting knowledge from data, including people from statistics, machine learning, neural networks, computer science, pattern recognition, database management, and other areas. The strategies adopted by people from these areas are often different, and a synergy results if this is recognised. IDA-2001 is intended to stimulate interaction between these different areas, so that more powerful tools emerge for extracting knowledge from data and a better understanding is developed of the process of intelligent data analysis.
It is the Fourth Symposium on Intelligent Data Analysis after the successful symposia IDA-99 (Amsterdam) , IDA-97 (London) , and IDA-95 (Baden-Baden).
The proceedings will be published in the Lecture Notes in Computer Science Series of Springer. The proceedings of Intelligent Data Analysis 97 and 99 appeared in this series as LNCS 1280 and LNCS 1642 . IDA 2001 will be included among the list of Forthcoming Proceedings of Springer .
We also plan to have a special issue of the Intelligent Data Analysis journal with extended versions of a number of papers presented during the symposium.
Contributed papers are invited on any relevant topic, including, but not restricted to
APPLICATIONS & TOOLS:
- analysis of different kinds of data (e.g., censored, temporal etc.)
- applications (e.g., commerce, engineering, finance, legal,
- manufacturing, medicine, public policy, science)
- assistants, intelligent agents for data analysis evaluation of IDA systems
- human-computer interaction in IDA
- IDA systems and tools
- information extraction, information retrieval
THEORY & GENERAL PRINCIPLES:
- analysis of IDA algorithms
- classification, projection, regression, optimization clustering
- data cleaning
- data pre-processing
- experiment design
- model specification, selection, estimation
- reasoning under uncertainty
- statistical strategy
- uncertainty and noise in data
ALGORITHMS & TECHNIQUES:
- Bayesian inference and influence diagrams
- bootstrap and randomization
- causal modeling
- data mining
- decision analysis
- exploratory data analysis
- automated data analysis
- fuzzy, neural and evolutionary appraoches
- knowledge-based analysis
- machine learning
- statistical pattern recognition
For further information, please contact Gabriela Guimaraes