ACL RD-TEC 1.0 Summarization of C04-1132

Paper Title:
LEARNING A ROBUST WORD SENSE DISAMBIGUATION MODEL USING HYPERNYMS IN DEFINITION SENTENCES

Authors: Kiyoaki Shirai and Tsunekazu Yagi

Other assigned terms:

  • ambiguity
  • approach
  • baseline model
  • bayes model
  • case
  • collocation
  • concept
  • concept dictionary
  • content words
  • corpora
  • data set
  • data sparseness
  • dictionaries
  • dictionary
  • disambiguation model
  • document
  • edr corpus
  • estimation
  • experimental results
  • extraction patterns
  • f-measure
  • fact
  • feature
  • feature set
  • feature vector
  • human intervention
  • hypernym
  • interpolation
  • japanese sentences
  • knowledge
  • likelihood
  • meaning
  • meanings
  • method
  • naive bayes model
  • natural language
  • nlp applications
  • nlp tasks
  • parts-of-speech
  • posterior
  • posterior probability
  • precision
  • prior probability
  • probabilistic model
  • probabilistic models
  • probability
  • process
  • relation
  • semantic
  • semantic classes
  • sense disambiguation model
  • sense-tagged corpora
  • sense-tagged corpus
  • sentence
  • sentences
  • statistics
  • support vector
  • svm model
  • symbol
  • target word
  • term
  • test data
  • thesaurus
  • training
  • training corpus
  • training data
  • training instance
  • verb
  • word
  • word frequency
  • word sense
  • word senses
  • word types
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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