Foundations of Intelligent Systems (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
747
Utgivningsdatum
2017-06-14
Upplaga
1st ed. 2017
Förlag
Springer International Publishing AG
Medarbetare
Kryszkiewicz, Marzena (ed.), Appice, Annalisa (ed.), Slezak, Dominik (ed.), Rybinski, Henryk (ed.), Skowron, Andrzej (ed.), Ras, Zbigniew W. (ed.)
Illustratör/Fotograf
Bibliographie
Illustrationer
182 Illustrations, black and white; XXIX, 747 p. 182 illus.
Dimensioner
234 x 156 x 39 mm
Vikt
1071 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783319604374
Foundations of Intelligent Systems (häftad)

Foundations of Intelligent Systems

23rd International Symposium, ISMIS 2017, Warsaw, Poland, June 26-29, 2017, Proceedings

Häftad Engelska, 2017-06-14
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This book constitutes the proceedings of the 23rd International Symposium on Foundations of Intelligent Systems, ISMIS 2017, held in Warsaw, Poland, in June 2017. The 56 regular and 15 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers include both theoretical and practical aspects of machine learning, data mining methods, deep learning, bioinformatics and health informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining. In addition, four special sessions were organized; namely, Special Session on Big Data Analytics and Stream Data Mining, Special Session on Granular and Soft Clustering for Data Science, Special Session on Knowledge Discovery with Formal Concept Analysis and Related Formalisms, and Special Session devoted to ISMIS 2017 Data Mining Competition on Trading Based on Recommendations, which was launched as a part of the conference.
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Innehållsförteckning

Machine learning.- data mining methods.- deep learning, bioinformatics and health informatics.- intelligent information systems.- knowledge-based system.- mining temporal, spatial and spatio-temporal data.- text and Web mining.- big data analytics and stream data mining.- granular and soft clustering for data science.- knowledge discovery with formal concept analysis and related formalisms.- data mining competition on trading based on recommendations.