Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

March 31, 2012

DS 2012 : The 15th International Conference on Discovery Science

Filed under: Conferences,Data Mining,Machine Learning — Patrick Durusau @ 4:09 pm

DS 2012 : The 15th International Conference on Discovery Science

Important Dates:

Important Dates for Submissions

Full paper submission: 17 th May, 2012
Author notification: 8th July, 2012
Camera-ready papers due: 20th July, 2012

Important dates for all DS 2012 attendees

Deadline for early registration: 30th August, 2012
DS 2012 conference dates: 29-31 October, 2012

From the call for papers:

DS-2012 will be collocated with ALT-2012, the 23rd International Conference on Algorithmic Learning Theory. The two conferences will be held in parallel, and will share their invited talks.

DS 2012 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.

We invite submissions of research papers addressing all aspects of discovery science. We particularly welcome contributions that discuss the application of data analysis, data mining and other support techniques for scientific discovery including, but not limited to, biomedical, astronomical and other physics domains.

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

I looked very briefly at prior proceedings. If those are any indication, this should be a very good conference.

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