ACL RD-TEC 1.0 Summarization of W03-0433
Paper Title:
A STACKED, VOTED, STACKED MODEL FOR NAMED ENTITY RECOGNITION
A STACKED, VOTED, STACKED MODEL FOR NAMED ENTITY RECOGNITION
Authors: Dekai Wu and Grace Ngai and Marine Carpuat
Primarily assigned technology terms:
- ada-boost
- adaboost
- algorithm
- approximation
- boosting
- categorization
- chinese word segmentation
- chunker
- chunking
- classification
- classifier
- classifier combination
- classifiers
- disambiguation
- entity extraction
- entity recognition
- error rate reduction
- forward match
- identification
- information extraction
- information retrieval
- language processing
- learner
- learning
- learning algorithm
- machine learning
- machine learning algorithm
- machine translation
- message understanding
- morphological analysis
- named entity recognition
- named-entity recognition
- natural language processing
- part-of-speech tagger
- part-of-speech tagging
- preprocessing
- processing
- rate reduction
- recognition
- rule learning
- rule-based machine
- segmentation
- sense disambiguation
- support vector machines
- tagger
- tagging
- text categorization
- transformation-based learning
- voting
- weak classifier
- word segmentation
- word sense disambiguation
Other assigned terms:
- approach
- bias
- case
- case information
- characters
- chinese word
- chunk
- chunk tag
- chunks
- common word lexicon
- concept
- development set
- dutch
- english part-of-speech
- error rate
- f-measure
- fact
- feature
- gazetteer
- gazetteer information
- gold standard
- knowledge
- labeling
- learning paradigm
- lexicon
- local maxima
- message
- message understanding conference
- method
- model performance
- named entities
- named entity
- named-entity
- names
- natural language
- ordered list
- part-of-speech
- part-of-speech tags
- prefixes and suffixes
- proper names
- sentence
- sentence boundaries
- statistics
- stem
- suffixes
- support vector
- svm model
- svms
- tags
- test data
- text
- toolkit
- trained model
- training
- training and test data
- training corpus
- training set
- understanding
- word
- word sense
- word types
- words
