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» Improving distant supervision using inference learning
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 10 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
ACL
2009
13 years 7 months ago
Unsupervised Learning of Narrative Schemas and their Participants
We describe an unsupervised system for learning narrative schemas, coherent sequences or sets of events (arrested(POLICE,SUSPECT), convicted( JUDGE, SUSPECT)) whose arguments are ...
Nathanael Chambers, Dan Jurafsky
HIS
2008
13 years 11 months ago
Towards a Highly Scalable Hybrid Metaheuristic for Haplotype Inference Under Parsimony
Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This ...
Stefano Benedettini, Luca Di Gaspero, Andrea Roli
EMNLP
2009
13 years 7 months ago
Improving Web Search Relevance with Semantic Features
Most existing information retrieval (IR) systems do not take much advantage of natural language processing (NLP) techniques due to the complexity and limited observed effectivenes...
Yumao Lu, Fuchun Peng, Gilad Mishne, Xing Wei, Ben...
ECAI
2000
Springer
14 years 2 months ago
Naive Bayes and Exemplar-based Approaches to Word Sense Disambiguation Revisited
Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...
Gerard Escudero, Lluís Màrquez, Germ...