Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
A Statistical View on Bilingual Lexicon Extraction: From Parallel Corpora to Non-parallel Corpora
AMTA '98 Proceedings of the Third Conference of the Association for Machine Translation in the Americas on Machine Translation and the Information Soup
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Computational Linguistics
Base Noun Phrase translation using web data and the EM algorithm
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Improving Machine Translation Performance by Exploiting Non-Parallel Corpora
Computational Linguistics
AsianIR '03 Proceedings of the sixth international workshop on Information retrieval with Asian languages - Volume 11
Weakly supervised named entity transliteration and discovery from multilingual comparable corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Feature-based method for document alignment in comparable news corpora
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Chinese terminology extraction using EM-Based transfer learning method
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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In this paper, we present an unsupervised hybrid model which combines statistical, lexical, linguistic, contextual, and temporal features in a generic EM-based framework to harvest bilingual terminology from comparable corpora through comparable document alignment constraint. The model is configurable for any language and is extensible for additional features. In overall, it produces considerable improvement in performance over the baseline method. On top of that, our model has shown promising capability to discover new bilingual terminology with limited usage of dictionaries.