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» Learning Markov Logic Networks Using Structural Motifs
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IJCAI
2007
13 years 6 months ago
Recursive Random Fields
A formula in first-order logic can be viewed as a tree, with a logical connective at each node, and a knowledge base can be viewed as a tree whose root is a conjunction. Markov l...
Daniel Lowd, Pedro Domingos
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
13 years 6 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
WWW
2011
ACM
12 years 11 months ago
Web information extraction using Markov logic networks
In this paper, we consider the problem of extracting structured data from web pages taking into account both the content of individual attributes as well as the structure of pages...
Sandeepkumar Satpal, Sahely Bhadra, Sundararajan S...
NN
2006
Springer
13 years 5 months ago
Self-organizing neural networks to support the discovery of DNA-binding motifs
Identification of the short DNA sequence motifs that serve as binding targets for transcription factors is an important challenge in bioinformatics. Unsupervised techniques from t...
Shaun Mahony, Panayiotis V. Benos, Terry J. Smith,...
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 5 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos