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KDD
2002
ACM
136views Data Mining» more  KDD 2002»
16 years 5 days 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
14 years 6 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»
16 years 5 days 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
15 years 2 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»
15 years 3 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