ACL RD-TEC 1.0 Summarization of W04-1201
Paper Title:
RECOGNIZING NAMES IN BIOMEDICAL TEXTS USING HIDDEN MARKOV MODEL AND SVM PLUS SIGMOID
RECOGNIZING NAMES IN BIOMEDICAL TEXTS USING HIDDEN MARKOV MODEL AND SVM PLUS SIGMOID
Primarily assigned technology terms:
- abbreviation resolution
- algorithm
- bayes classifier
- binding
- biomedical named entity recognition
- boundary detection
- classifier
- entity recognition
- entity recognition system
- error analysis
- hidden markov
- hidden markov model
- hmm-based approach
- identification
- learning
- learning approaches
- machine learning
- machine learning approaches
- markov model
- naive bayes
- naive bayes classifier
- name resolution
- named entity recognition
- post-processing
- recognition
- recognition system
- svm-based recognition
- taggers
Other assigned terms:
- abbreviation
- abbreviations
- ambiguity
- annotation
- annotation scheme
- approach
- bias
- biomedical domain
- cache
- data sparseness
- data sparseness problem
- dictionaries
- dictionary
- discourse
- disjunction
- document
- evaluations
- f-measure
- fact
- feature
- feature set
- genia
- genia corpus
- head noun
- heuristic
- heuristic rules
- hmm state feature
- kappa
- mapping
- modifier
- named entity
- names
- noun phrases
- part-ofspeech
- semantic
- sense ambiguity
- sentence
- sparseness problem
- state feature
- suffix
- synonym
- test data
- training
- training data
- word
- word formation
- word formation pattern
