Discovery Science [electronic resource] : 14th International Conference, DS 2011, Espoo, Finland, October 5-7, 2011. Proceedings / edited by Tapio Elomaa, Jaakko Hollmén, Heikki Mannila.
By: Elomaa, Tapio [editor.].
Contributor(s): Hollmén, Jaakko [editor.] | Mannila, Heikki [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 6926Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XIII, 381 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244773.Subject(s): Computer science | Computer software | Database management | Data mining | Information storage and retrieval systems | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Information Storage and Retrieval | Information Systems Applications (incl. Internet) | Database Management | Data Mining and Knowledge Discovery | Algorithm Analysis and Problem ComplexityDDC classification: 006.3 Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the refereed proceedings of the 14th International Conference on Discovery Science, DS 2011, held in Espoo, Finland, in October 2011 - co-located with ALT 2011, the 22nd International Conference on Algorithmic Learning Theory. The 24 revised full papers presented together with 5 invited lectures were carefully revised and selected from 56 submissions. The papers cover a wide range including 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.
This book constitutes the refereed proceedings of the 14th International Conference on Discovery Science, DS 2011, held in Espoo, Finland, in October 2011 - co-located with ALT 2011, the 22nd International Conference on Algorithmic Learning Theory. The 24 revised full papers presented together with 5 invited lectures were carefully revised and selected from 56 submissions. The papers cover a wide range including 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.
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