ACL RD-TEC 1.0 Summarization of W01-0719

Paper Title:
COMBINING LINGUISTIC AND MACHINE LEARNING TECHNIQUES FOR EMAIL SUMMARIZATION

Authors: Smaranda Muresan and Evelyne Tzoukermann and Judith L. Klavans

Other assigned terms:

  • approach
  • bayes model
  • brown corpus
  • case
  • characters
  • classification task
  • coherence
  • compounds
  • concept
  • determiners
  • document
  • document content
  • email
  • email message
  • fact
  • feature
  • feature vector
  • feature vectors
  • forest
  • genre
  • grammaticality
  • heuristics
  • hypotheses
  • hypothesis
  • inflection
  • information gain
  • knowledge
  • linear combination
  • linguistic
  • linguistic intuition
  • linguistic knowledge
  • meaning
  • measure
  • measures
  • message
  • metadata
  • method
  • modifier
  • n-gram
  • n-grams
  • natural language
  • nlp applications
  • nlp tasks
  • noise
  • normalization factor
  • noun phrase
  • noun phrase length
  • noun phrases
  • nouns
  • opinion
  • paragraph
  • phrase
  • phrase structure
  • precision
  • preposition
  • prepositional phrases
  • prepositions
  • probabilistic models
  • process
  • production rules
  • query
  • relation
  • rule set
  • rule sets
  • search strategy
  • semantic
  • semantic content
  • sentence
  • sentences
  • source text
  • sparse data
  • suffix
  • syntactic constituents
  • syntactic head
  • syntactic unit
  • tags
  • technical terms
  • technique
  • technologies
  • terms
  • test data
  • text
  • tf \* idf
  • training
  • training set
  • tree
  • trees
  • user
  • verb
  • web documents
  • word
  • word sense
  • wordnet
  • wordnet package
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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