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99
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ACL
2007
15 years 2 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li
COLT
1993
Springer
15 years 4 months ago
Learning Binary Relations Using Weighted Majority Voting
In this paper we demonstrate how weighted majority voting with multiplicative weight updating can be applied to obtain robust algorithms for learning binary relations. We first pre...
Sally A. Goldman, Manfred K. Warmuth
DEXAW
2008
IEEE
185views Database» more  DEXAW 2008»
15 years 7 months ago
Axiom-Based Feedback Cycle for Relation Extraction in Ontology Learning from Text
—The ontology learning from text cycle consists of the consecutive phases of term, synonym, concept, taxonomy and relation extraction. In this paper, a proposal towards the unsup...
Witold Abramowicz, Maria Vargas-Vera, Marek Wisnie...
112
Voted
ATAL
2008
Springer
15 years 2 months ago
A statistical relational model for trust learning
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Achim Rettinger, Matthias Nickles, Volker Tresp
88
Voted
ESWS
2008
Springer
15 years 2 months ago
Learning Highly Structured Semantic Repositories from Relational Databases:
Abstract. Relational databases are valuable sources for ontology learning. Methods and tools have been proposed to generate ontologies from such structured input. However, a major ...
Farid Cerbah