ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Computational Linguistics - Special issue on using large corpora: I
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
A class-based approach to word alignment
Computational Linguistics
A program for aligning sentences in bilingual corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
K-vec: a new approach for aligning parallel texts
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Automatic detection of omissions in translations
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Automatic generation of Japanese–English bilingual thesauri based on bilingual corpora
Journal of the American Society for Information Science and Technology - Research Articles
Improving word alignment using syntactic dependencies
SSST '08 Proceedings of the Second Workshop on Syntax and Structure in Statistical Translation
Preliminary study into query translation for patent retrieval
PaIR '10 Proceedings of the 3rd international workshop on Patent information retrieval
Bilingual chunk alignment based on interactional matching and probabilistic latent semantic indexing
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
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In this paper, a method for the word alignment of English-Chinese corpus based on chunks is proposed. The chunks of English sentences are identified firstly. Then the chunk boundaries of Chinese sentences are predicted by the translations of English chunks and heuristic information. The ambiguities of Chinese chunk boundaries are resolved by the coterminous words in English chunks. With the chunk aligned bilingual corpus, a translation relation probability is proposed to align words. Finally, we evaluate our system by real corpus and present the experiment results.