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» Practical Preference Relations for Large Data Sets
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ECSQARU
2001
Springer
15 years 7 months ago
General Preferential Entailments as Circumscriptions
Abstract A (general) preferential entailment is defined by a “preference relation” among “states”. States can be either interpretations or sets of interpretations, or “c...
Yves Moinard
OTM
2007
Springer
15 years 9 months ago
Hawkeye: A Practical Large Scale Demonstration of Semantic Web Integration
Abstract. We discuss our DLDB knowledge base system and evaluate its capability in processing a very large set of real-world Semantic Web data. Using DLDB, we have constructed the ...
Zhengxiang Pan, Abir Qasem, Sudhan Kanitkar, Fabia...
TNN
2010
176views Management» more  TNN 2010»
14 years 10 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
BMCBI
2006
93views more  BMCBI 2006»
15 years 3 months ago
A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database
Background: Many of the most popular pre-processing methods for Affymetrix expression arrays, such as RMA, gcRMA, and PLIER, simultaneously analyze data across a set of predetermi...
Simon Katz, Rafael A. Irizarry, Xue Lin, Mark Trip...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 3 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui