ACL RD-TEC 1.0 Summarization of W99-0623
Paper Title:
EXPLOITING DIVERSITY IN NATURAL LANGUAGE PROCESSING: COMBINING PARSERS
EXPLOITING DIVERSITY IN NATURAL LANGUAGE PROCESSING: COMBINING PARSERS
Authors: John C. Henderson and Eric Brill
Primarily assigned technology terms:
- algorithm
- automated parsing
- bayes classification
- bayes classifier
- bayes constituent combination
- classification
- classifier
- classifiers
- constituent combination
- constituent voting
- database
- decision making
- entity recognition
- hybridization
- language and speech processing
- language processing
- learning
- machine learning
- machine translation
- modeling
- naive bayes
- naive bayes classification
- naive bayes classifier
- naive bayes classifiers
- naive bayes techniques
- named entity recognition
- natural language processing
- non-parametric switching
- non-parametric switching technique
- parametric hybridization
- parser
- parser combination
- parser switching
- parsers
- parsing
- part of speech tagging
- partitioning
- pcfg parser
- penn treebank parsing
- processing
- recognition
- speech processing
- speech recognition
- speech tagging
- statistical parsers
- statistical parsing
- tagging
- treebank parsing
- voting
Other assigned terms:
- approach
- bias
- case
- classification error
- classification error rate
- community
- database query
- development set
- error rate
- estimation
- evaluation measures
- events
- f-measure
- feature
- grammar
- grammars
- hypotheses
- hypothesis
- hypothesis test
- lemma
- measure
- measures
- method
- named entity
- natural language
- noise
- noise rate
- noun phrases
- oracle
- parse
- parse tree
- parser performance
- parsing accuracy
- part of speech
- pcfg
- penn treebank
- precision
- probabilistic model
- probabilities
- probability
- procedure
- process
- query
- root node
- semantic
- semantic information
- sentence
- sentences
- similarity metric
- technique
- test set
- theory
- training
- training set
- tree
- treebank
- treebank parse
- trees
- wall street journal corpus
