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» Identifying graphs from noisy and incomplete data
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WWW
2003
ACM
14 years 8 months ago
Text joins in an RDBMS for web data integration
The integration of data produced and collected across autonomous, heterogeneous web services is an increasingly important and challenging problem. Due to the lack of global identi...
Luis Gravano, Panagiotis G. Ipeirotis, Nick Koudas...
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
13 years 8 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen
UAI
2004
13 years 9 months ago
Identifying Conditional Causal Effects
This paper concerns the assessment of the effects of actions from a combination of nonexperimental data and causal assumptions encoded in the form of a directed acyclic graph in w...
Jin Tian
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
INFOCOM
1995
IEEE
13 years 11 months ago
Automatic Alarm Correlation for Fault Identification
In communication networks, a large number of alarms exist to signal any abnormal behavior of the network. As network faults typically result in a number of alarms, correlating the...
Isabelle Rouvellou, George W. Hart