ACL RD-TEC 1.0 Summarization of W04-2408
Paper Title:
MODELING CATEGORY STRUCTURES WITH A KERNEL FUNCTION
MODELING CATEGORY STRUCTURES WITH A KERNEL FUNCTION
Authors: Hiroya Takamura and Yuji Matsumoto and Hiroyasu Yamada
Primarily assigned technology terms:
- algorithm
- categorization
- classification
- classifiers
- clustering
- computing
- disambiguation
- em algorithm
- feature extraction
- fisher kernel
- hp-top kernel
- indexing
- kernel
- kernels
- latent semantic indexing
- learning
- likelihood estimation
- linear kernel
- maximum likelihood
- maximum likelihood estimation
- modeling
- parameterization
- polynomial kernel
- semantic indexing
- sense disambiguation
- support vector machines
- svm computation
- text categorization
- unsupervised clustering
- word sense disambiguation
Other assigned terms:
- case
- category structure
- clusters
- computational complexity
- computational overhead
- derivation
- distribution
- document
- document length
- estimation
- experimental setting
- fact
- feature
- feature set
- feature space
- feature vector
- feature vectors
- gaussian mixture
- generative model
- generative models
- generative probability
- joint probability
- kernel function
- large training
- latent semantic
- likelihood
- log-likelihood
- mapping
- method
- posterior
- posterior probability
- probabilistic model
- probabilistic models
- probability
- probability density
- probability distribution
- probability distributions
- proposition
- relation
- semantic
- statistics
- support vector
- svms
- term
- terms
- text
- training
- training data
- training dataset
- training examples
- training set
- training time
- unlabeled examples
- weight vector
- word
- word sense
- words
