ACL RD-TEC 1.0 Summarization of P99-1036

Paper Title:
A PART OF SPEECH ESTIMATION METHOD FOR JAPANESE UNKNOWN WORDS USING A STATISTICAL MODEL OF MORPHOLOGY AND CONTEXT

Other assigned terms:

  • alphabet
  • approach
  • baseline model
  • bigram
  • bigram model
  • case
  • character bigram model
  • character sequence
  • character type
  • characters
  • chinese characters
  • cross entropy
  • data sparseness
  • dictionaries
  • dictionary
  • distribution
  • dynamic programming procedure
  • edr corpus
  • entropy
  • estimation
  • events
  • f-measure
  • fact
  • feature-based approach
  • function words
  • grammatical function
  • hapax legomena
  • information source
  • japanese corpus
  • japanese sentences
  • japanese word
  • joint probability
  • kanji
  • katakana
  • knowledge
  • language model
  • length distribution
  • linguistic
  • measures
  • method
  • morphological knowledge
  • ngram
  • noun phrases
  • nouns
  • orthography
  • out-of-vocabulary rate
  • part of speech
  • particles
  • perplexity
  • poisson distribution
  • precision
  • prediction accuracy
  • probabilistic framework
  • probabilities
  • probability
  • procedure
  • pronunciation
  • punctuation
  • punctuation marks
  • relative frequency
  • roman alphabet
  • segmentation accuracy
  • segmented corpus
  • sentence
  • sentences
  • speech information
  • spelling model
  • statistical model
  • substring
  • suffix
  • surface form
  • symbol
  • symbols
  • tagged corpus
  • tagging accuracy
  • tagging precision
  • tags
  • technical terms
  • term
  • terms
  • test data
  • test set
  • tokens
  • training
  • training and test data
  • training corpus
  • training data
  • training set
  • unigram
  • unigram model
  • unknown word model
  • verb
  • word
  • word bigram model
  • word model
  • word morphology
  • word segmentation accuracy
  • word sequence
  • word type
  • word-based language model
  • words
  • writing system

Extracted Section Types:


This page last edited on 10 May 2017.

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