Fourteenth International Conference on Discovery Science, Espoo, Finland
5 October 2011 - 5 October 2011
Finland
The Fourteenth International Conference on Discovery Science will be held from 5 to 7 October 2011 in Espoo, Finland.
Discovery science is a methodology where the process of discovery is handled by computer science. It is more descriptive than predictive, focusing on curiosity rather than accuracy. This means that discovery-based methodologies are often viewed in contrast to traditional scientific practice, where hypotheses are formed before close examination of experimental data.
Data mining is the most common tool used in discovery science, and is applied to data from diverse fields of study such as DNA analysis, climate modeling, nuclear reaction modeling and others. The use of data mining in discovery science often makes use of specialised machine learning algorithms for automated hypothesis forming and automated theorem proving.
The scope of the conference will include the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis and the theory of learning, as well as their application to knowledge discovery.For further information, please visit: http://ds2011.org/cfp.html(opens in new window)
Discovery science is a methodology where the process of discovery is handled by computer science. It is more descriptive than predictive, focusing on curiosity rather than accuracy. This means that discovery-based methodologies are often viewed in contrast to traditional scientific practice, where hypotheses are formed before close examination of experimental data.
Data mining is the most common tool used in discovery science, and is applied to data from diverse fields of study such as DNA analysis, climate modeling, nuclear reaction modeling and others. The use of data mining in discovery science often makes use of specialised machine learning algorithms for automated hypothesis forming and automated theorem proving.
The scope of the conference will include the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis and the theory of learning, as well as their application to knowledge discovery.For further information, please visit: http://ds2011.org/cfp.html(opens in new window)