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Advances in Knowledge Discovery and Management : Volume 7 / / edited by Bruno Pinaud, Fabrice Guillet, Bruno Cremilleux, Cyril de Runz



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Titolo: Advances in Knowledge Discovery and Management : Volume 7 / / edited by Bruno Pinaud, Fabrice Guillet, Bruno Cremilleux, Cyril de Runz Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Edizione: 1st ed. 2018.
Descrizione fisica: 1 online resource (XIII, 147 p. 46 illus., 35 illus. in color.)
Disciplina: 006.312
Soggetto topico: Computational intelligence
Artificial intelligence
Data mining
Knowledge management
Computational Intelligence
Artificial Intelligence
Data Mining and Knowledge Discovery
Knowledge Management
Persona (resp. second.): PinaudBruno
GuilletFabrice
CremilleuxBruno
de RunzCyril
Note generali: Includes index.
Nota di contenuto: A Combined Approach for Ontology Enrichment from Textual and Open Data -- C-SPARQL Extension for Sampling RDF Graphs Streams -- Efficiency Analysis of ASP Encodings for Sequential Pattern Mining Tasks.
Sommario/riassunto: This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of “Knowledge Discovery and Management” (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories. The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC’2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.
Titolo autorizzato: Advances in Knowledge Discovery and Management  Visualizza cluster
ISBN: 3-319-65406-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299874303321
Lo trovi qui: Univ. Federico II
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Serie: Studies in Computational Intelligence, . 1860-949X ; ; 732