ACL RD-TEC 1.0 Summarization of W03-0429
Paper Title:
NAMED ENTITY RECOGNITION USING HUNDREDS OF THOUSANDS OF FEATURES
NAMED ENTITY RECOGNITION USING HUNDREDS OF THOUSANDS OF FEATURES
Authors: James Mayfield and Paul McNamee and Christine Piatko
Primarily assigned technology terms:
- algorithm
- binary classifier
- chunking
- classification
- classifier
- classifiers
- cubic kernel
- entity recognition
- hidden markov
- hidden markov models
- hmm tagger
- iterative method
- kernel
- likelihood estimate
- linear interpolation
- linear kernel
- maximum likelihood
- named entity recognition
- part-of-speech tagging
- recognition
- scoring
- smoothing
- supervised training
- support vector machine
- support vector machines
- syntactic chunking
- tag assignment
- tagger
- tagging
- tnt tagger
- tuning
Other assigned terms:
- approach
- break
- distribution
- document
- english language
- estimation
- fact
- feature
- feature set
- feature space
- implementation
- interpolation
- joint probability
- knowledge
- lattice
- likelihood
- markov models
- maximum likelihood estimate
- measure
- method
- named entity
- part-of-speech
- probabilities
- probability
- probability distributions
- probability estimate
- reuters corpus
- sentence
- sigmoid function
- support vector
- svms
- system performance
- tag set
- tags
- target language
- technique
- test data
- test set
- text
- theory
- training
- training and test data
- training data
- training phase
- training samples
- training set
- training time
- transition probabilities
- vector space
- vertex
- word
- words
