Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Identifying word correspondence in parallel texts
HLT '91 Proceedings of the workshop on Speech and Natural Language
Automating the acquisition of bilingual terminology
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
Two languages are more informative than one
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Aligning sentences in parallel corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
A program for aligning sentences in bilingual corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Aligning sentences in bilingual corpora using lexical information
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
A statistical approach to language translation
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Identification and classification of proper nouns in Chinese texts
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Sentence alignment using P-NNT and GMM
Computer Speech and Language
A method for multilingual text mining and retrieval using growing hierarchical self-organizing maps
Journal of Information Science
Multilingual document mining and navigation using self-organizing maps
Information Processing and Management: an International Journal
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To align bilingual texts becomes a crucial issue recently. Rather than using length-based or translation-based criterion, a part-of-speech-based criterion is proposed. We postulate that source texts and target texts should share the same concepts, ideas, entities, and events. Simulated annealing approach is used to implement this alignment algorithm. The preliminary experiments show good performance. Most importantly, the experimental objects are Chinese-English texts, which are selected from different language families.