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» Unsupervised Natural Language Processing Using Graph Models
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COLING
2002
14 years 11 months ago
A Graph Model for Unsupervised Lexical Acquisition
This paper presents an unsupervised method for assembling semantic knowledge from a part-ofspeech tagged corpus using graph algorithms. The graph model is built by linking pairs o...
Dominic Widdows, Beate Dorow
ICASSP
2011
IEEE
14 years 3 months ago
Unsupervised determination of efficient Korean LVCSR units using a Bayesian Dirichlet process model
Korean is an agglutinative language that does not have explicit word boundaries. It is also a highly inflective language that exhibits severe coarticulation effects. These charac...
Sakriani Sakti, Andrew M. Finch, Ryosuke Isotani, ...
EMNLP
2010
14 years 9 months ago
On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing
This paper introduces dual decomposition as a framework for deriving inference algorithms for NLP problems. The approach relies on standard dynamic-programming algorithms as oracl...
Alexander M. Rush, David Sontag, Michael Collins, ...
ICASSP
2008
IEEE
15 years 6 months ago
Unsupervised language model adaptation via topic modeling based on named entity hypotheses
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
Yang Liu, Feifan Liu
99
Voted
CVPR
2007
IEEE
16 years 1 months ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson