Formal Concept Analysis [electronic resource] : 10th International Conference, ICFCA 2012, Leuven, Belgium, May 7-10, 2012. Proceedings / edited by Florent Domenach, Dmitry Ignatov, Jonas Poelmans.
Contributor(s): Domenach, Florent [editor.]
| Ignatov, Dmitry [editor.] | Poelmans, Jonas [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Artificial Intelligence: 7278Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Edition: 1st ed. 2012.Description: XII, 309 p. 75 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642298929.Subject(s): Artificial intelligence | Software engineering | Data mining | Machine theory | Computer science -- Mathematics | Discrete mathematics | Algebra | Artificial Intelligence | Software Engineering | Data Mining and Knowledge Discovery | Formal Languages and Automata Theory | Discrete Mathematics in Computer Science | Order, Lattices, Ordered Algebraic StructuresAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: 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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