[Comp-neuro] Call For Papers - Discovery Science 2009

Pedro Pereira Rodrigues pprodrigues at liaad.up.pt
Thu Dec 4 15:35:57 CET 2008


Call For Papers

Discovery Science 2009

http://ds09.liaad.up.pt/


The 12th International Conference on Discovery Science (DS-2009) will be 
held in Porto, Portugal, on 3-5 October 2009. The proceedings of DS-2009 
will appear in the Lecture Notes in Artificial Intelligence Series by 
Springer-Verlag.

DS-2009 provides an open forum for intensive discussions and exchange of 
new ideas among researchers working in the area of Discovery Science. 
The scope of the conference includes the development and analysis of 
methods for automatic scientific knowledge discovery, machine learning, 
intelligent data analysis, theory of learning, as well as their 
application to knowledge discovery. Very welcome are papers that focus 
on dynamic and evolving data, models and structures.

Welcome!


Important Dates

Mentoring program submission: 12 April 2009
Submission deadline: 10 May 2009
Notifications: 21 June 2009
Camera-ready copy: 10 July 2009
Conference: 3-5 October 2009


Collocated Event

DS-2009 will be collocated with ALT-2009, the 20th International 
Conference on Algorithmic Learning Theory. The two conferences will be 
held in parallel, and will share their invited talks.


Mentoring Program

Based on the success of the past four years, DS-2009 is featuring once 
again a mentoring program. Students or groups of students that work 
alone are invited to submit a paper draft no later than the mentoring 
deadline. They will receive comments from a PC member that will help 
them prepare their final submission.


Student Award

An excellent student paper will be selected to receive the Carl Smith Award.
The award carries a scholarship prize of 555 Euros.


Submission Topics

We invite submissions of research papers addressing all aspects of 
discovery science. We particularly welcome contributions that discuss 
the application of scientific knowledge discovery and other support 
techniques including, but not limited to, biomedical, astronomical, 
space, chemistry and other physics domains.
A paper submission must be formatted according to the layout supplied by 
Springer-Verlag for the Lecture Notes in Computer Science series. Papers 
may contain up to fifteen (15) pages. Possible topics include, but are 
not limited to:

Logic and philosophy of scientific discovery
Knowledge discovery, machine learning and statistical methods
Ubiquitous Knowledge Discovery
Data Streams, Evolving Data and Models
Change Detection and Model Maintenance
Active Knowledge Discovery
Learning from Text and web mining
Information extraction from scientific literature
Knowledge discovery from heterogeneous, unstructured and multimedia data
Knowledge discovery in network and link data
Knowledge discovery in social networks
Data and knowledge visualization
Spatial/Temporal Data
Mining graphs and structured data
Planning to Learn
Knowledge transfer
Computational Creativity
Human-machine interaction for knowledge discovery and management
Biomedical knowledge discovery, analysis of micro-array and gene 
deletion data
Machine Learning for High-Performance Computing, Grid and Cloud Computing
Applications of the above techniques to natural or social sciences
Other applications of the above technique


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