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» Learning Bayesian Networks from Incomplete Databases
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SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
14 years 11 days ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
KDD
2008
ACM
121views Data Mining» more  KDD 2008»
14 years 11 months ago
Reconstructing chemical reaction networks: data mining meets system identification
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Yong Ju Cho, Naren Ramakrishnan, Yang Cao
SIGOPS
2010
162views more  SIGOPS 2010»
13 years 9 months ago
Visual and algorithmic tooling for system trace analysis: a case study
Despite advances in the application of automated statistical and machine learning techniques to system log and trace data there will always be a need for human analysis of machine...
Wim De Pauw, Steve Heisig
SASO
2009
IEEE
14 years 5 months ago
Optimising Sensor Layouts for Direct Measurement of Discrete Variables
An optimal sensor layout is attained when a limited number of sensors are placed in an area such that the cost of the placement is minimised while the value of the obtained inform...
X. Rosalind Wang, George Mathews, Don Price, Mikha...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
14 years 11 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel