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» Techniques of Cluster Algorithms in Data Mining
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BIBM
2007
IEEE
159views Bioinformatics» more  BIBM 2007»
16 years 22 days ago
Predicting Future High-Cost Patients: A Real-World Risk Modeling Application
Health care data from patients in the Arizona Health Care Cost Containment System, Arizona’s Medicaid program, provides a unique opportunity to exploit state-of-the-art data pro...
Sai T. Moturu, William G. Johnson, Huan Liu
ICML
2002
IEEE
16 years 7 months ago
Kernels for Semi-Structured Data
Semi-structured data such as XML and HTML is attracting considerable attention. It is important to develop various kinds of data mining techniques that can handle semistructured d...
Hisashi Kashima, Teruo Koyanagi
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
16 years 6 months ago
From Data To Insight: The Community Of Multimedia Agents
Multimedia Data Mining requires the ability to automatically analyze and understand the content. The Community of Multimedia Agents project (COMMA) is devoted to creating an open ...
Gang Wei, Valery A. Petrushin, Anatole Gershman
PPOPP
2010
ACM
16 years 3 months ago
A distributed placement service for graph-structured and tree-structured data
Effective data placement strategies can enhance the performance of data-intensive applications implemented on high end computing clusters. Such strategies can have a significant i...
Gregory Buehrer, Srinivasan Parthasarathy, Shirish...
BIBE
2003
IEEE
116views Bioinformatics» more  BIBE 2003»
15 years 11 months ago
An Assessment of a Metric Space Database Index to Support Sequence Homology
Hierarchical metric-space clustering methods have been commonly used to organize proteomes into taxonomies. Consequently, it is often anticipated that hierarchical clustering can ...
Rui Mao, Weijia Xu, Neha Singh, Daniel P. Miranker