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» Challenges for Data Mining in Distributed Sensor Networks
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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 9 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
ISDA
2008
IEEE
14 years 3 months ago
Combining Clustering and Bayesian Network for Gene Network Inference
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
Suhaila Zainudin, Safaai Deris
IPPS
2008
IEEE
14 years 3 months ago
Scalable data dissemination using hybrid methods
Web server scalability can be greatly enhanced via hybrid data dissemination methods that use both unicast and multicast. Hybrid data dissemination is particularly promising due t...
Wenhui Zhang, Vincenzo Liberatore, Jonathan Beaver...
CLUSTER
2006
IEEE
14 years 3 months ago
Positioning Dynamic Storage Caches for Transient Data
Simulations, experiments and observatories are generating a deluge of scientific data. Even more staggering is the ever growing application demand to process and assimilate these...
Sudharshan S. Vazhkudai, Douglas Thain, Xiaosong M...
SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
14 years 9 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar