株式会社極東書店トップ ＞ 商品一覧 ＞ 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. 2014 ed.
商品詳細
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. 2014 ed.
・ISBN 978-3-319-13185-6 paper EUR 99.99
￥26,726.- (税込) ※（※）価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
| 著者・編者 | Peng, Wen-Chih / Wang, Haixun / Bailey, James / Tseng, Vincent S. / Ho, Tu Bao / Zhou, Zhi-Hua / Chen, Arbee L.P. (eds.), |
|---|---|
| シリーズ | (Lecture Notes in Computer Science) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2014 |
| ページ数 | 833 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-14280＞ |
解説
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.