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» Optimizing Local Probability Models for Statistical Parsing
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ACL
2001
13 years 6 months ago
Joint and Conditional Estimation of Tagging and Parsing Models
This paper compares two different ways of estimating statistical language models. Many statistical NLP tagging and parsing models are estimated by maximizing the (joint) likelihoo...
Mark Johnson
VTC
2006
IEEE
13 years 11 months ago
Feasible Link Statistics for Adaptive Ad Hoc Networks
— The dynamic nature of ad hoc networks advocates the use of adaptive schemes to optimize network performance. Such adaptive schemes require local observations of prevailing netw...
Senan J. Doyle, Timothy K. Forde, Linda Doyle
ACL
1996
13 years 6 months ago
A New Statistical Parser Based on Bigram Lexical Dependencies
This paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. Standard bigram probability estimation techniqu...
Michael Collins
EMNLP
2007
13 years 6 months ago
Probabilistic Models of Nonprojective Dependency Trees
A notable gap in research on statistical dependency parsing is a proper conditional probability distribution over nonprojective dependency trees for a given sentence. We exploit t...
David A. Smith, Noah A. Smith
EMNLP
2004
13 years 6 months ago
Dependencies vs. Constituents for Tree-Based Alignment
Given a parallel parsed corpus, statistical treeto-tree alignment attempts to match nodes in the syntactic trees for a given sentence in two languages. We train a probabilistic tr...
Daniel Gildea