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» Large Scale Data Mining: Challenges and Responses
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ICDM
2005
IEEE
135views Data Mining» more  ICDM 2005»
15 years 11 months ago
Bit Reduction Support Vector Machine
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
DAWAK
2011
Springer
14 years 6 months ago
OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses
In recent years, there has been a large increase in the amount of spatial data obtained from remote sensing, GPS receivers, communication terminals and other domains. Data warehous...
Ganesh Viswanathan, Markus Schneider
EDBT
2009
ACM
277views Database» more  EDBT 2009»
15 years 10 months ago
G-hash: towards fast kernel-based similarity search in large graph databases
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
EDBT
2006
ACM
122views Database» more  EDBT 2006»
16 years 6 months ago
TQuEST: Threshold Query Execution for Large Sets of Time Series
Effective and efficient data mining in time series databases is essential in many application domains as for instance in financial analysis, medicine, meteorology, and environmenta...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...
CIKM
2008
Springer
15 years 8 months ago
SNIF TOOL: sniffing for patterns in continuous streams
Continuous time-series sequence matching, specifically, matching a numeric live stream against a set of predefined pattern sequences, is critical for domains ranging from fire spr...
Abhishek Mukherji, Elke A. Rundensteiner, David C....