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» Applying Grid Technologies to Distributed Data Mining
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WAIM
2007
Springer
14 years 2 months ago
Distributed, Hierarchical Clustering and Summarization in Sensor Networks
We propose DHCS, a method of distributed, hierarchical clustering and summarization for online data analysis and mining in sensor networks. Different from the acquisition and aggre...
Xiuli Ma, Shuangfeng Li, Qiong Luo, Dongqing Yang,...
WWW
2008
ACM
13 years 7 months ago
Discovering geographical-specific interests from web click data
As the Internet continues to play an important role in many business applications, it becomes vital to increase the competitive edge by offering geographically tailored contents t...
Chang Sheng, Wynne Hsu, Mong-Li Lee
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
14 years 8 days ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
GCC
2006
Springer
13 years 11 months ago
Design of Computational Grid-based Intelligence ART1 Classification System for Bioinformatics Applications
Computational Grid technology has been noticed as an issue to solve large-scale bioinformatics-related problems and improves data accuracy and processing speed on multiple computa...
Kyu Cheol Cho, Yong Beom Ma, Jong Sik Lee
HICSS
2003
IEEE
176views Biometrics» more  HICSS 2003»
14 years 1 months ago
Ad-Hoc Association-Rule Mining within the Data Warehouse
Many organizations often underutilize their already constructed data warehouses. In this paper, we suggest a novel way of acquiring more information from corporate data warehouses...
Svetlozar Nestorov, Nenad Jukic