Trends and Applications in Knowledge Discovery and Data Mining: Pakdd 2014 International Workshops: Danth, Bdm, Mobisocial, Bigec, Cloudsd, Msmv-Mbi,

ISBN-13: 9783319131856 / Angielski / Miękka / 2014 / 833 str.

Wen-Chih Peng; Haixun Wang; James Bailey

Opis

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.

Spis treści

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.