Formal Concept Analysis [electronic resource] : 10th International Conference, ICFCA 2012, Leuven, Belgium, May 7-10, 2012. Proceedings / edited by Florent Domenach, Dmitry I. Ignatov, Jonas Poelmans.

Contributor(s): Domenach, Florent [editor.] | Ignatov, Dmitry I [editor.] | Poelmans, Jonas [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 7278Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012Description: XII, 309 p. 75 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642298929Subject(s): Computer science | Software engineering | Computational complexity | Data mining | Artificial intelligence | Algebra | Computer Science | Artificial Intelligence (incl. Robotics) | Software Engineering | Data Mining and Knowledge Discovery | Mathematical Logic and Formal Languages | Discrete Mathematics in Computer Science | Order, Lattices, Ordered Algebraic StructuresAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 LOC classification: Q334-342TJ210.2-211.495Online resources: Click here to access online In: Springer eBooksSummary: This book constitutes the refereed proceedings of the 10th International Conference on Formal Concept Analysis, ICFCA 2012, held in Leuven, Belgium in May 2012. The 20 revised full papers presented together with 6 invited talks were carefully reviewed and selected from 68 submissions. The topics covered in this volume range from recent advances in machine learning and data mining; mining terrorist networks and revealing criminals; concept-based process mining; to scalability issues in FCA and rough sets.
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This book constitutes the refereed proceedings of the 10th International Conference on Formal Concept Analysis, ICFCA 2012, held in Leuven, Belgium in May 2012. The 20 revised full papers presented together with 6 invited talks were carefully reviewed and selected from 68 submissions. The topics covered in this volume range from recent advances in machine learning and data mining; mining terrorist networks and revealing criminals; concept-based process mining; to scalability issues in FCA and rough sets.

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