ACL RD-TEC 1.0 Summarization of H92-1023
Paper Title:
DECISION TREE MODELS APPLIED TO THE LABELING OF TEXT WITH PARTS-OF-SPEECH
DECISION TREE MODELS APPLIED TO THE LABELING OF TEXT WITH PARTS-OF-SPEECH
Authors: Ezra Black and Fred Jelinek and John Lafferty and Robert Mercer and Salim Roukos
Primarily assigned technology terms:
- algorithm
- categorization
- clustering
- coding
- decision tree
- decision tree method
- decision trees
- em algorithm
- forward-backward algorithm
- greedy algorithm
- hidden markov
- hidden markov model
- hmm method
- information clustering
- language modeling
- markov model
- maximum entropy
- maximum entropy model
- maximum likelihood
- modeling
- smoothing
- splitting
- statistical language modeling
- tagging
- tree method
- word bigram
Other assigned terms:
- ambiguity
- approach
- bigram
- bigram model
- binary features
- binary tree
- brown corpus
- case
- clustering procedure
- corpora
- dictionaries
- dictionary
- distribution
- english text
- entropy
- entropy models
- error rate
- events
- experimental results
- hmm model
- joint distribution
- labeling
- leaf
- lexicon
- likelihood
- linguists
- long-distance dependencies
- maximum entropy models
- method
- multiword expressions
- mutual information
- part-of-speech
- parts-of-speech
- preposition
- probabilities
- probability
- procedure
- process
- queries
- semantic
- sentence
- sentences
- statistical significance
- statistics
- syntactic features
- tag set
- tagging model
- tags
- technique
- test data
- test set
- text
- theory
- training
- training corpora
- training corpus
- training data
- training text
- tree
- treebank
- trees
- trigram
- uniform distribution
- verb
- vocabulary
- word
- word corpus
- words
