ACL RD-TEC 1.0 Summarization of W06-1641
Paper Title:
SENTIMENT RETRIEVAL USING GENERATIVE MODELS
SENTIMENT RETRIEVAL USING GENERATIVE MODELS
Authors: Koji Eguchi and Victor Lavrenko
Primarily assigned technology terms:
- automatic annotation
- automatic extraction
- classification
- classifiers
- computational linguistics
- information retrieval
- language modeling
- language modeling approach
- language processing
- modeling
- natural language processing
- processing
- ranking
- retrieving
- sentence retrieval
- sentiment classification
- sentiment retrieval
- smoothing
- stemmer
- tuning
- weighting
Other assigned terms:
- annotation
- annotation scheme
- annotator
- approach
- association for computational linguistics
- bag of words
- bpref evaluation measure
- case
- chunks
- data set
- discourse
- distribution
- document
- estimation
- evaluation data
- evaluation measure
- events
- generative model
- generative models
- human annotator
- information need
- knowledge
- language model
- language models
- likelihood
- linear combination
- linguistics
- manual annotation
- mean average precision
- measure
- measures
- method
- model parameter
- model parameters
- natural language
- natural-language
- negation
- opinion
- opinions
- passage
- phrase
- phrase level
- polarity
- polarity specification
- positive polarity
- precision
- probabilities
- probability
- process
- queries
- query
- relation
- relative frequency
- retrieval model
- retrieval performance
- retrieval task
- seed
- seed words
- sentence
- sentence level
- sentences
- sentiment
- sentiment word
- stopword list
- stress
- structural information
- suffix
- term
- term distribution
- terms
- test data
- testing set
- text
- topic language model
- topics
- training
- training corpus
- training data
- training set
- unigram
- unigram language model
- user
- vocabulary
- word
- words
