ACL RD-TEC 1.0 Summarization of P03-2041
Paper Title:
LEARNING NON-ISOMORPHIC TREE MAPPINGS FOR MACHINE TRANSLATION
LEARNING NON-ISOMORPHIC TREE MAPPINGS FOR MACHINE TRANSLATION
Primarily assigned technology terms:
- agenda-based parsing
- algorithm
- bottom-up chart parsing
- chart parsing
- decoding
- dynamic programming
- em algorithm
- em training
- em\/viterbi
- expectation-maximization
- inside-outside algorithm
- learning
- machine translation
- machine translation systems
- matching
- modeling
- parsers
- parsing
- parsing algorithm
- phrase-based translation
- post-processing
- statistical machine translation
- statistical mt
- summarization
- synchronous tree substitution
- synchronous treeadjoining grammar
- transducers
- translation systems
- tree substitution
- viterbi
- viterbi algorithm
- word-to-word translation
Other assigned terms:
- adjunction
- analogy
- approach
- break
- case
- chunks
- conditional probability
- conditional probability distribution
- context-free grammar
- dependency grammars
- dependency trees
- derivation
- derivation tree
- derivation trees
- derivations
- distribution
- elementary tree
- forest
- formalism
- formalisms
- french
- generation
- generation process
- grammar
- grammars
- hypotheses
- joint probability
- joint probability model
- language model
- language pair
- local maximum
- mapping
- mappings
- method
- nonterminals
- paragraph
- paraphrase
- parse
- parse forest
- preposition
- priori
- probabilistic model
- probabilities
- probability
- probability distribution
- probability estimates
- probability model
- procedure
- process
- root node
- runtime
- selectional preferences
- sentence
- sentence pair
- sentences
- statistical model
- subgraph
- substitution grammar
- subtree
- subtrees
- symbol
- syntax
- syntax and semantics
- target language
- terms
- topology
- training
- training time
- translation accuracy
- translation models
- translations
- tree
- tree structure
- tree substitution grammar
- trees
- vertex
- viterbi parse
- word
- words
