ACL RD-TEC 1.0 Summarization of W06-2908
Paper Title:
SEMANTIC ROLE RECOGNITION USING KERNELS ON WEIGHTED MARKED ORDERED LABELED TREES
SEMANTIC ROLE RECOGNITION USING KERNELS ON WEIGHTED MARKED ORDERED LABELED TREES
Authors: Jun'ichi Kazama and Kentaro Torisawa
Primarily assigned technology terms:
- accurate semantic role labeling
- algorithm
- argument recognition
- binary classifier
- charniak parser
- classification
- classification method
- classifier
- classifiers
- computational linguistics
- computational natural language learning
- dynamic programming
- fast argument recognition
- feature engineering
- fragment extraction
- inner product
- kernel
- kernels
- language learning
- learning
- learning methods
- local classification
- machine learning
- machine learning methods
- mining
- natural language learning
- parser
- parsing
- pre-processing
- processing
- recognition
- recognizer
- role assignment
- semantic role labeling
- subtree inclusion
- support vector machines
- svm classifier
- syntactic analysis
- tree kernel
- tree kernels
- tree mining
- tuning
- vector representation
- weighting
Other assigned terms:
- approach
- association for computational linguistics
- case
- conll-x
- development set
- dynamic programming procedure
- evaluation set
- fact
- feature
- feature space
- feature vector
- implementation
- kernel function
- labeling
- linguistics
- mapping
- maps
- meaning
- measure
- method
- natural language
- oracle
- parse
- parse tree
- parsing accuracy
- phrase
- pp attachment
- probability
- probability value
- procedure
- propbank
- recognition accuracy
- relation
- relative clauses
- role labeling
- root node
- runtime
- semantic
- semantic role
- sentence
- sentences
- sigmoid function
- subtree
- subtrees
- support vector
- svms
- tags
- technique
- test set
- time complexity
- training
- training data
- training examples
- training set
- training time
- tree
- tree structure
- trees
- verb
- word
- words
