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» Learning for Semantic Parsing
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AIIA
1995
Springer
15 years 5 months ago
Learning Programs in Different Paradigms using Genetic Programming
Genetic Programming (GP) is a method of automatically inducing programs by representing them as parse trees. In theory, programs in any computer languages can be translated to par...
Man Leung Wong, Kwong-Sak Leung
ACL
2009
14 years 11 months ago
Bayesian Learning of a Tree Substitution Grammar
Tree substitution grammars (TSGs) offer many advantages over context-free grammars (CFGs), but are hard to learn. Past approaches have resorted to heuristics. In this paper, we le...
Matt Post, Daniel Gildea
ICASSP
2009
IEEE
15 years 8 months ago
Combining discriminative re-ranking and co-training for parsing Mandarin speech transcripts
Discriminative reranking has been able to significantly improve parsing performance, and co-training has proven to be an effective weakly supervised learning algorithm to bootstr...
Wen Wang
ACL
1996
15 years 2 months ago
Fast Parsing Using Pruning and Grammar Specialization
We show how a general grammar may be automatically adapted for fast parsing of utterances from a specific domain by means of constituent pruning and grammar specialization based o...
Manny Rayner, David M. Carter
ACL
2000
15 years 2 months ago
Automatic Labeling of Semantic Roles
e, the system labels constituents with either abstract semantic roles such as AGENT or PATIENT, or more domain-specific semantic roles such as SPEAKER, MESSAGE, and TOPIC. The syst...
Daniel Gildea, Daniel Jurafsky