ACL RD-TEC 1.0 Summarization of P06-1080
Paper Title:
SELF-ORGANIZING N-GRAM MODEL FOR AUTOMATIC WORD SPACING
SELF-ORGANIZING N-GRAM MODEL FOR AUTOMATIC WORD SPACING
Authors: Seong-Bae Park and Yoon-Shik Tae and Se-Young Park
Primarily assigned technology terms:
- algorithm
- analyzer
- automatic word spacing
- binary classification
- classification
- computational linguistics
- computing
- decision tree
- decision tree induction
- decision trees
- hidden markov
- hidden markov model
- induction
- information processing
- information retrieval
- knowledge construction and maintenance
- korean language processing
- language and speech processing
- language modeling
- language processing
- learning
- learning algorithms
- likelihood estimate
- machine learning
- machine learning algorithms
- markov model
- maximum entropy
- maximum entropy approach
- maximum entropy model
- maximum likelihood
- modeling
- morphological analysis
- morphological analyzer
- natural language processing
- pos tagging
- probabilistic method
- processing
- sampling
- sequence tagging
- smoothing
- smoothing technique
- smoothing techniques
- speech processing
- support vector machine
- support vector machines
- tagging
- tree induction
- viterbi
- viterbi algorithm
Other assigned terms:
- approach
- association for computational linguistics
- bigram
- bigram model
- binary classification task
- case
- classification task
- composition
- context size
- corpora
- corpus size
- data set
- data sparseness
- dimensionality
- distribution
- entropy
- experimental results
- fact
- french
- knowledge
- korean language
- kullback-leibler divergence
- language model
- language models
- likelihood
- linguistic
- linguistic knowledge
- linguistics
- local context
- maximum likelihood estimate
- method
- methodology
- natural language
- natural language sentences
- particle
- performance comparison
- probabilistic model
- probabilities
- probability
- processing time
- sentence
- sentences
- statistical approach
- statistics
- support vector
- syllables
- symbols
- tag sequence
- tagging task
- tags
- technique
- test set
- training
- training instance
- training set
- tree
- trees
- trigram
- trigram model
- unigram
- unigram model
- window size
- word
- word order
- words
