Rough Sets and Knowledge Technology [electronic resource] : 6th International Conference, RSKT 2011, Banff, Canada, October 9-12, 2011. Proceedings / edited by JingTao Yao, Sheela Ramanna, Guoyin Wang, Zbigniew Suraj.
By: Yao, JingTao [editor.].
Contributor(s): Ramanna, Sheela [editor.] | Wang, Guoyin [editor.] | Suraj, Zbigniew [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 6954Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XVIII, 771 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244254.Subject(s): Computer science | Database management | Data mining | Artificial intelligence | Optical pattern recognition | Computer Science | Artificial Intelligence (incl. Robotics) | Data Mining and Knowledge Discovery | Database Management | Mathematical Logic and Formal Languages | Computation by Abstract Devices | Pattern RecognitionDDC classification: 006.3 Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the refereed proceedings of the 6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011, held in Banff, Canada, in September 2011. The 89 revised full papers presented together with 3 keynote lectures and 1 invited tutorial session were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on attribute reduction and feature selection, generalized rough set models, machine learning with rough and hybrid techniques, knowledge technology and intelligent systems and applications.
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This book constitutes the refereed proceedings of the 6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011, held in Banff, Canada, in September 2011. The 89 revised full papers presented together with 3 keynote lectures and 1 invited tutorial session were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on attribute reduction and feature selection, generalized rough set models, machine learning with rough and hybrid techniques, knowledge technology and intelligent systems and applications.
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