ACL RD-TEC 1.0 Summarization of P03-1066

Paper Title:
UNSUPERVISED LEARNING OF DEPENDENCY STRUCTURE FOR LANGUAGE MODELING

Authors: Jianfeng Gao and Hisami Suzuki

Other assigned terms:

  • annotated corpora
  • annotation
  • approach
  • backoff
  • baseline model
  • bias
  • bigram
  • bigram model
  • bunsetsu
  • case
  • chinese word
  • compounds
  • conditional probabilities
  • corpora
  • data sparseness
  • data sparseness problem
  • decision rule
  • dependency relation
  • dependency relations
  • dependency structure
  • entropy
  • error rate
  • estimation
  • function words
  • heuristic
  • hypothesis
  • implementation
  • interpolation
  • knowledge
  • language model
  • likelihood
  • linguistic
  • linguistic constraints
  • linguistic structure
  • mapping
  • mapping table
  • maps
  • measure
  • method
  • model parameters
  • model probability
  • model size
  • modeling decision
  • n-gram
  • n-grams
  • noise
  • parse
  • parse tree
  • parsing model
  • part-of-speech
  • penn treebank
  • phrase
  • probabilities
  • probability
  • raw text corpus
  • relation
  • semantic
  • semantic roles
  • sentence
  • sparseness problem
  • structure of a sentence
  • syntactic constraints
  • syntactic relation
  • syntactic structure
  • syntactic trees
  • tag set
  • tags
  • technique
  • test data
  • text
  • text corpus
  • training
  • training corpus
  • training data
  • tree
  • treebank
  • trees
  • trigram
  • trigram model
  • undirected graph
  • unigram
  • window size
  • word
  • word category
  • word string
  • word trigram
  • word trigram model
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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