ACL RD-TEC 1.0 Summarization of W04-0203
Paper Title:
USING A PROBABILISTIC MODEL OF DISCOURSE RELATIONS TO INVESTIGATE WORD ORDER VARIATION
USING A PROBABILISTIC MODEL OF DISCOURSE RELATIONS TO INVESTIGATE WORD ORDER VARIATION
Primarily assigned technology terms:
- approximation
- automatic classification
- bootstrapping
- classification
- classifier
- classifiers
- discourse marker
- discourse segmentation
- discourse structuring
- language generation
- language generation system
- listing
- logistic regression
- natural language generation
- regression
- segmentation
- structuring
- surface realization
- topicalization
Other assigned terms:
- annotation
- approach
- case
- coherence
- coherence relation
- community
- contrast relation
- corpora
- corpus-based research
- correlation
- correlations
- cue words
- discourse
- discourse context
- discourse entities
- discourse function
- discourse markers
- discourse relation
- discourse relations
- discourse segment
- discourse structure
- discourse tree
- distribution
- events
- fact
- feature
- feature set
- feature value
- feature vectors
- feature weights
- generation
- generation system
- inferences
- information structure
- inter-annotator agreement
- interpretation
- left-dislocation
- lexical discourse
- lexical feature
- lexical features
- likelihood
- linguistic
- linguistic features
- logistic regression model
- mapping
- meaning
- meanings
- measure
- measures
- method
- model fit
- natural language
- natural languages
- order variation
- probabilistic model
- probabilities
- proposition
- propositional content
- propositions
- prosody
- regression model
- relation
- rhetorical relations
- segment boundaries
- segments
- semantic
- semantic content
- sentence
- sentences
- statistical model
- statistical models
- stress
- syntactic form
- syntactic properties
- syntax
- technique
- terms
- text
- theories
- theory
- tokens
- tree
- tree structure
- utterance
- word
- word order
- word order variation
- words
