ACL RD-TEC 1.0 Summarization of W06-2204
Paper Title:
TRANSDUCTIVE PATTERN LEARNING FOR INFORMATION EXTRACTION
TRANSDUCTIVE PATTERN LEARNING FOR INFORMATION EXTRACTION
Authors: Brian McLernon and Nicholas Kushmerick
Primarily assigned technology terms:
- algorithm
- boosting
- bootstrapping
- boundary detection
- classification
- computing
- conditional random fields
- ensemble learning
- entity classification
- entity recognition
- exhaustive search
- expectation maximization
- expectation maximization algorithm
- extraction algorithm
- fragment identification
- heuristic search
- hidden markov
- hidden markov models
- identification
- information extraction
- iterative process
- learning
- learning algorithm
- learning algorithms
- learning process
- learning task
- learning technique
- machine learning
- matching
- maximization algorithm
- multi-field extraction
- named entity classification
- named entity recognition
- normalization
- pattern generation
- pattern learning
- post-processing
- probabilistic finite-state
- recognition
- recursive scoring
- scoring
- scoring function
- scoring method
- search
- semi-supervised algorithm
- semi-supervised learning
Other assigned terms:
- approach
- binary features
- case
- community
- confidence scores
- convergence
- corpora
- document
- document set
- extraction patterns
- feature
- generation
- generation strategy
- heuristic
- heuristics
- implementation
- labeled training data
- labeling
- large labeled training corpora
- likelihood
- markov models
- meaning
- measure
- measures
- method
- named entities
- named entity
- named entity corpus
- names
- precision
- prior probability
- probabilities
- probability
- procedure
- process
- punctuation
- scoring metric
- search space
- seed
- set size
- tags
- technique
- terms
- test data
- test set
- text
- tokens
- training
- training corpora
- training data
- training documents
- training set
- training set size
- untagged corpus
- utterance
- wildcard
