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KDD
1994
ACM
140views Data Mining» more  KDD 1994»
13 years 11 months ago
A Comparison of Pruning Methods for Relational Concept Learning
Pre-Pruning and Post-Pruning are two standard methods of dealing with noise in concept learning. Pre-Pruning methods are very efficient, while Post-Pruning methods typically are m...
Johannes Fürnkranz
DICTA
2003
13 years 9 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang
KDD
1998
ACM
181views Data Mining» more  KDD 1998»
13 years 12 months ago
Approaches to Online Learning and Concept Drift for User Identification in Computer Security
The task in the computer security domain of anomaly detection is to characterize the behaviors of a computer user (the `valid', or `normal' user) so that unusual occurre...
Terran Lane, Carla E. Brodley
AI
1999
Springer
13 years 7 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
ICGI
2010
Springer
13 years 5 months ago
Learning Context Free Grammars with the Syntactic Concept Lattice
The Syntactic Concept Lattice is a residuated lattice based on the distributional structure of a language; the natural representation based on this is a context sensitive formalism...
Alexander Clark