Paper Info
Title
Mining Models for Failing Behaviors
Abstract
Understanding the causes for failure is one of the bottlenecks in the educational process. Despite failure prediction has been pursued, models behind that prediction, most of the time, do not give a deep insight about failure causes. In this paper, we introduce a new method for mining fault trees automatically, and show that these models are a precious help on identifying direct and indirect causes for failure. An experimental study is presented in order to access the drawbacks of the proposed method.
Year
DOI
Venue
2009
10.1109/ISDA.2009.122
ISDA
Keywords
Field
DocType
failing behaviors,deep insight,failure prediction,mining fault tree,experimental study,failure cause,new method,mining models,indirect cause,educational process,precious help,decision trees,logic gates,association rules,data mining,fault trees,fault tree,accuracy
Object-oriented modeling,Decision tree,Data mining,Failure causes,Logic gate,Computer science,Association rule learning,Artificial intelligence,Fault tree analysis,Machine learning
Conference
ISSN
ISBN
Citations 
2164-7143
978-0-7695-3872-3
0
PageRank 
References 
Authors
0.34
8
1
Name
Order
Citations
PageRank
Cláudia Antunes116116.57