Fr. 135.00

Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers

Englisch · Taschenbuch

Versand in der Regel in 6 bis 7 Wochen

Beschreibung

Mehr lesen

This book constitutes the refereed proceedings at PAKDD Workshops 2014, held in conjunction with the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014.
The 73 revised papers presented were carefully reviewed and selected from 179 submissions. The workshops affiliated with PAKDD 2014 include: Data Analytics for Targeted Healthcare, DANTH; Data Mining and Decision Analytics for Public Health and Wellness, DMDA-Health; Biologically Inspired Data Mining Techniques, BDM; Mobile Data Management, Mining, and Computing on Social Networks, MobiSocial; Big Data Science and Engineering on E-Commerce, BigEC; Cloud Service Discovery, CloudSD; Mobile Sensing, Mining and Visualization for Human Behavior Inferences, MSMV-HBI; Scalable Dats Analytics: Theory and Algorithms, SDA; Algorithms for Large-Scale Information Processing in Knowledge Discovery, ALSIP; Data Mining in Social Networks, SocNet; Data Mining in Biomedical Informatics and Healthcare, DMBIH; and Pattern Mining and Application of Big Data, BigPMA.

Inhaltsverzeichnis

Data Analytics for Targeted Healthcare, DANTH.- Data Mining and Decision Analytics for Public Health and Wellness, DMDA-Health.- Biologically Inspired Data Mining Techniques, BDM.- Mobile Data Management, Mining, and Computing on Social Networks, MobiSocial.- Big Data Science and Engineering on E-Commerce, BigEC.- Cloud Service Discovery, CloudSD.- Mobile Sensing, Mining and Visualization for Human Behavior Inferences, MSMV-HBI.- Scalable Dats Analytics: Theory and Algorithms, SDA.- Algorithms for Large-Scale Information Processing in Knowledge Discovery, ALSIP.- Data Mining in Social Networks, SocNet.- Data Mining in Biomedical Informatics and Healthcare, DMBIH.- Pattern Mining and Application of Big Data, BigPMA.

Produktdetails

Mitarbeit James Bailey (Herausgeber), James Bailey et al (Herausgeber), Arbee L. P. Chen (Herausgeber), Arbee L.P. Chen (Herausgeber), Tu Bao Ho (Herausgeber), Tu-Bao Ho (Herausgeber), Wen-Chih Peng (Herausgeber), Vincent S. Tseng (Herausgeber), Haixu Wang (Herausgeber), Haixun Wang (Herausgeber), Zhi-Hua Zhou (Herausgeber)
Verlag Springer, Berlin
 
Sprache Englisch
Produktform Taschenbuch
Erschienen 01.01.2014
 
EAN 9783319131856
ISBN 978-3-31-913185-6
Seiten 833
Abmessung 158 mm x 235 mm x 240 mm
Gewicht 1270 g
Illustration XXI, 833 p. 348 illus.
Serien Lecture Notes in Computer Science
Lecture Notes in Artificial Intelligence
Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence
Lecture Notes in Computer Science
Lecture Notes in Artificial Intelligence
Themen Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik

C, Künstliche Intelligenz, Data Mining, Artificial Intelligence, angewandte informatik, Data Warehousing, Informationsrückgewinnung, Information Retrieval, Social Network, Wissensbasierte Systeme, Expertensysteme, Computeranwendungen in Industrie und Technologie, computer science, Information Retrieval, Web Intelligence, Information Systems Applications (incl. Internet), Health Informatics, Computer and Information Systems Applications, Application software, Data Mining and Knowledge Discovery, Health & safety aspects of IT, Internet searching, Expert systems / knowledge-based systems, Information Storage and Retrieval, Applied computing, semi-supervised learning, Semantic Web Technologies

Kundenrezensionen

Zu diesem Artikel wurden noch keine Rezensionen verfasst. Schreibe die erste Bewertung und sei anderen Benutzern bei der Kaufentscheidung behilflich.

Schreibe eine Rezension

Top oder Flop? Schreibe deine eigene Rezension.

Für Mitteilungen an CeDe.ch kannst du das Kontaktformular benutzen.

Die mit * markierten Eingabefelder müssen zwingend ausgefüllt werden.

Mit dem Absenden dieses Formulars erklärst du dich mit unseren Datenschutzbestimmungen einverstanden.