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» Learning relational dependency networks in hybrid domains
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ICML
2006
IEEE
14 years 11 months ago
Learning hierarchical task networks by observation
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Negin Nejati, Pat Langley, Tolga Könik
WWW
2005
ACM
14 years 11 months ago
Hybrid semantic tagging for information extraction
The semantic web is expected to have an impact at least as big as that of the existing HTML based web, if not greater. However, the challenge lays in creating this semantic web an...
Ronen Feldman, Binyamin Rosenfeld, Moshe Fresko, B...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 11 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
ICML
2006
IEEE
14 years 11 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
ML
2008
ACM
100views Machine Learning» more  ML 2008»
13 years 10 months ago
Generalized ordering-search for learning directed probabilistic logical models
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendri...