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Trends and Applications in Knowledge Discovery and Data Mining : PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF, Auckland, New Zealand, April 19, 2016, Revised Selected Papers / / edited by Huiping Cao, Jinyan Li, Ruili Wang



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Titolo: Trends and Applications in Knowledge Discovery and Data Mining : PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF, Auckland, New Zealand, April 19, 2016, Revised Selected Papers / / edited by Huiping Cao, Jinyan Li, Ruili Wang Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Edizione: 1st ed. 2016.
Descrizione fisica: 1 online resource (XIII, 282 p. 84 illus.)
Disciplina: 006.3
Soggetto topico: Artificial intelligence
Data mining
Health informatics
Information storage and retrieval
Application software
Computers
Artificial Intelligence
Data Mining and Knowledge Discovery
Health Informatics
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
Computation by Abstract Devices
Persona (resp. second.): CaoHuiping
LiJinyan, Ph. D.
WangRuili
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Biologically Inspired Data Mining Techniques, BDM -- Machine Learning for Sensory Data Analysis, MLSDA -- Predictive Analytics for Critical Care, PACC -- Data Mining in Business and Finance, WDMBF.
Sommario/riassunto: This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2016, held in conjunction with PAKDD, the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented were carefully reviewed and selected from 38 submissions. The workshops affiliated with PAKDD 2016 include: Biologically Inspired Data Mining Techniques, BDM; Machine Learning for Sensory Data Analysis, MLSDA; Predictive Analytics for Critical Care, PACC; as well as Data Mining in Business and Finance, WDMBF.
Titolo autorizzato: Trends and Applications in Knowledge Discovery and Data Mining  Visualizza cluster
ISBN: 3-319-42996-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910485035003321
Lo trovi qui: Univ. Federico II
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Serie: Lecture Notes in Artificial Intelligence ; ; 9794