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New Frontiers in Mining Complex Patterns : 4th International Workshop, NFMCP 2015, Held in Conjunction with ECML-PKDD 2015, Porto, Portugal, September 7, 2015, Revised Selected Papers - 1st ed. 2016

By: (Edited by) Corrado Loglisci , (Edited by) Elio Masciari , (Edited by) Giuseppe Manco , (Edited by) Michelangelo Ceci , (Edited by) Zbigniew W. Ras

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Ksh 8,100.00

Format: Paperback / Softback

ISBN-10: 3319393146

ISBN-13: 9783319393148

Edition: 1st ed. 2016

Series: Lecture Notes in Artificial Intelligence

Publisher: Springer International Publishing AG

Imprint: Springer International Publishing AG

Country of Manufacture: CH

Country of Publication: GB

Publication Date: May 18th, 2016

Print length: 239 Pages

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This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2015, held in conjunction with ECML-PKDD 2015 in Porto, Portugal, in September 2015. The 15 revised full papers presented together with  one invited talk were carefully reviewed and selected from 19 submissions. Theyillustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: data stream mining, classification, mining complex data, and sequences.

This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2015, held in conjunction with ECML-PKDD 2015 in Porto, Portugal, in September 2015.

The 15 revised full papers presented together with  one invited talk were carefully reviewed and selected from 19 submissions. They illustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: data stream mining, classification, mining complex data, and sequences.


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