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Building a Better Backtrace: Techniques for Postmortem Program Analysis
Building Better Backtrace Techniques Postmortem Program Analysis
2016/5/25
After a program has crashed, it can be difficult to reconstruct why the failure occurred, or what actions led to the error. We propose a family of analysis techniques that use the evidence left behind...
Static Analysis Techniques for Predicting the Behavior of Active Database Rules
Static Analysis Techniques Predicting Behavior Active Database Rules
2016/5/24
Methods are given for statically analyzing sets of database production rules to determine if the rules are (1) guaranteed to terminate, (2) guaranteed to produce a unique nal database state, and (3) ...
Data Survey and Management Techniques in Civil Protection Emergencies
Earthquakes Forest fire GIS
2015/7/7
Calamitous events cause modifications in soil morphology and damages in infrastructures. The knowledge of these modifications
can be very useful for the Civil Protection operations. However, survey o...
Supporting Topic Map Creation Using Data Mining Techniques
Supporting Topic Map Creation Data Mining Techniques
2009/12/7
There is an increasing interest in automating creation of semantic structures, especially topic maps, by taking advantage of existing, structured information resources. This article gives a preview of...
Rapid Techniques for Performance Estimation of Processors
Rapid Techniques Performance Estimation Processors
2008/5/18
Current techniques for processor performance evaluation, which rely on using instruction set simulators to estimate the performance for each of the processors, may not be feasible due to the large amo...
A SURVEY OF TEXT CLUSTERING TECHNIQUES USED FOR WEB MINING
information retrieval algorithms machine learning
2005/1/12
this paper contains an overview of basic formulations and approaches to clustering. Then it presents two important clustering paradigms: a bottom-up agglomerative technique, which collects similar doc...
The k-nearest neighbours (kNN) is a simple but effective method for classification. Its major drawbacks are (1) low efficiency, and (2) dependency on the selection of a “good value” for k. In this pap...