Identifying word correspondence in parallel texts
HLT '91 Proceedings of the workshop on Speech and Natural Language
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Looking for candidate translational equivalents in specialized, comparable corpora
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 2
Mining comparable bilingual text corpora for cross-language information integration
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Improving Machine Translation Performance by Exploiting Non-Parallel Corpora
Computational Linguistics
Finding translations for low-frequency words in comparable corpora
Machine Translation
Decompounding query keywords from compounding languages
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Extracting parallel sentences from comparable corpora using document level alignment
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Revisiting context-based projection methods for term-translation spotting in comparable corpora
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
EACL 2012 Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)
Bilingual lexicon extraction from comparable corpora using label propagation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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We present a first known result of high precision rare word bilingual extraction from comparable corpora, using aligned comparable documents and supervised classification. We incorporate two features, a context-vector similarity and a co-occurrence model between words in aligned documents in a machine learning approach. We test our hypothesis on different pairs of languages and corpora. We obtain very high F-Measure between 80% and 98% for recognizing and extracting correct translations for rare terms (from 1 to 5 occurrences). Moreover, we show that our system can be trained on a pair of languages and test on a different pair of languages, obtaining a F-Measure of 77% for the classification of Chinese-English translations using a training corpus of Spanish-French. Our method is therefore even potentially applicable to low resources languages without training data.