ACL RD-TEC 1.0 Summarization of W06-1653
Paper Title:
RELEVANCE FEEDBACK MODELS FOR RECOMMENDATION
RELEVANCE FEEDBACK MODELS FOR RECOMMENDATION
Authors: Masao Utiyama and Mikio Yamamoto
Primarily assigned technology terms:
- approximation
- classification
- computational linguistics
- cross validation
- cross-language information retrieval
- database
- editing
- em method
- information retrieval
- interpolation method
- language modeling
- language modeling approach
- language processing
- learning
- learning algorithms
- linear interpolation
- machine learning
- machine learning algorithms
- maximum-likelihood
- modeling
- natural language processing
- optimization
- parameter estimation
- porter stemmer
- probability estimation
- processing
- ranking
- rating
- ratio test
- recommender
- reporting
- score calculation
- search
- searching
- smoothing
- stemmer
- support vector machines
- validation
- vector space model
Other assigned terms:
- analogy
- approach
- association for computational linguistics
- cache
- case
- distance measure
- distribution
- document
- encyclopedia
- estimation
- evaluations
- feature
- implementation
- information need
- interpolation
- knowledge
- kullback-leibler divergence
- language models
- linguistics
- log-likelihood
- log-likelihood ratio
- mapping
- measure
- measures
- method
- multinomial distribution
- multinomial model
- natural language
- parameter space
- perplexity
- positive and negative examples
- precision
- probabilities
- probability
- probability distribution
- query
- query model
- relation
- search space
- smoothing parameter
- standard deviation
- support vector
- terms
- test data
- text
- tokens
- training
- training and test data
- training data
- user
- vector space
- wikipedia
- word
- word sequences
- words
