Conferences In Information Security
| Conference Name | International Symposium on Intelligent Data Analysis |
|---|---|
| Venue | Lyon, France |
| URL | http://ida09.liris.cnrs.fr/ |
| Submission Deadline | 30-Mar-10 |
| Conference Date | 31 August - 2 September 2010 |
| Sponsership/Publisher | |
| Aim/Scope/Research Area |
Topics of interestContributed papers are invited on any relevant topic, including, but not restricted to:
Algorithms & Techniques (Machine Learning, Data Mining, Statistics): Artificial neural networks - Bayesian networks - Heuristic methods Optimization problems - Case-based reasoning - Computational models of human learning Computational learning theory - Cooperative learning - Unsupervised learning Decision and induction Evolutionary computation Grammatical inference Incremental and on-line learning Information retrieval and learning Knowledge acquisition and learning Data pre- and post-processing Data visualisation Statistical pattern recognition and analysis Performance and optimization Bootstrap and randomization Causal modeling Decision analysis Exploratory data analysis Knowledge-based analysis Classification, projection, regression, optimization clustering Data cleaning Model specification, selection, estimation Reasoning under uncertainty Uncertainty and noise in data Theoritical contributions (Data analysis principles, Data modeling):Data Mining theories Information retrieval restrictions Legal data analysis restrictions Innovative data analysis (models, information types, and objectives) Theoretical IDA issues New paradigms Analysis of IDA algorithms Applications Fields (Practical, Applied and Industrial Data Analysis):Analysis of different kinds of data (e.g., censored, temporal etc.) Applications (e.g., commerce, engineering, finance, legal, manufacturing, medicine, public policy, science, bioinformatics, biosurveillance) Assistants, intelligent agents for data analysis evaluation of IDA systems Human-computer interaction in IDA IDA systems and tools Information extraction, information retrieval Experiment design |