ACL RD-TEC 1.0 Summarization of P98-2191
Paper Title:
MAXIMUM ENTROPY MODEL LEARNING OF THE TRANSLATION RULES
MAXIMUM ENTROPY MODEL LEARNING OF THE TRANSLATION RULES
Authors: Kengo Sato and Masakazu Nakanishi
Primarily assigned technology terms:
- algorithm
- em algorithm
- feature selection
- feature selection algorithm
- forward-backward algorithm
- hidden markov
- hidden markov model
- inside-outside algorithm
- iterative algorithm
- iterative scaling
- lagrange multiplier
- language modeling
- language processing
- learning
- learning method
- machine translation
- markov model
- maximum entropy
- maximum entropy method
- maximum entropy model
- model learning
- modeling
- morphological analysis
- multilingual natural language processing
- natural language processing
- optimization
- parameter estimation
- processing
- selection algorithm
- word-to-word translation
Other assigned terms:
- approach
- co-occurrence
- co-occurrence information
- conditional probability
- context free grammar
- corpora
- dictionaries
- dictionary
- distribution
- entropy
- estimation
- feature
- grammar
- heuristic
- implementation
- infinitive form
- japanese word
- language model
- log-likelihood
- machine-readable dictionary
- maximum entropy principle
- measure
- method
- morphological information
- natural language
- parallel corpora
- part-of-speech
- part-of-speech tag
- pcfg
- probabilistic model
- probability
- probability distribution
- sentence
- sentences
- statistical natural language
- termination condition
- training
- training corpora
- training data
- translation rules
- uniform distribution
- word
- words
