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KDD
2002
ACM
136views Data Mining» more  KDD 2002»
14 years 9 months ago
Relational Markov models and their application to adaptive web navigation
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
Corin R. Anderson, Pedro Domingos, Daniel S. Weld
WWW
2011
ACM
13 years 3 months ago
From actors, politicians, to CEOs: domain adaptation of relational extractors using a latent relational mapping
We propose a method to adapt an existing relation extraction system to extract new relation types with minimum supervision. Our proposed method comprises two stages: learning a lo...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 9 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
FLAIRS
2007
13 years 11 months ago
Fuzzy Temporal Relations for Fault Management
In this paper we shall introduce an approach that forms a basis for temporal data mining. A relation algebra is applied for the purpose of representing simultaneously dependencies...
Hanna Bauerdick, Björn Gottfried
KDD
1994
ACM
140views Data Mining» more  KDD 1994»
14 years 22 days 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