ACL RD-TEC 1.0 Summarization of E06-1026
Paper Title:
LATENT VARIABLE MODELS FOR SEMANTIC ORIENTATIONS OF PHRASES
LATENT VARIABLE MODELS FOR SEMANTIC ORIENTATIONS OF PHRASES
Authors: Hiroya Takamura and Takashi Inui and Manabu Okumura
Primarily assigned technology terms:
- algorithm
- approximation
- bayes classifier
- case assignment
- classification
- classification method
- classifier
- clustering
- computing
- cross-validation
- document classification
- em algorithm
- expectation-maximization
- expectation-maximization algorithm
- feature extraction
- identification
- indexing
- latent semantic indexing
- learning
- learning method
- naive bayes
- naive bayes classifier
- optimization
- phrase level classification
- rating
- semantic indexing
- semi-supervised learning
- splitting
Other assigned terms:
- 10-fold cross-validation
- adjective
- annotators
- baseline model
- bayes model
- case
- classification accuracy
- classification performance
- classification tasks
- cluster
- clusters
- computational model
- conditional probability
- context information
- contingency table
- convergence
- density function
- derivation
- dictionary
- distribution
- distributional similarity
- document
- estimation
- fact
- feature
- gaussian distribution
- generative probability
- generative probability model
- inter-annotator agreement
- joint probability
- latent semantic
- latent semantic space
- likelihood
- linguistic
- linguistic resources
- log-likelihood
- method
- naive bayes model
- nouns
- optimization problem
- phrase
- phrase level
- polarity
- posterior
- prediction task
- probabilistic model
- probabilities
- probability
- probability density
- probability density function
- probability model
- query
- representations
- seed
- seed words
- semantic
- semantic space
- sentences
- statistics
- tags
- technique
- term
- theory
- thesaurus
- training
- training dataset
- training time
- tree
- trigram
- verb
- word
- word sequences
- words
