Paper: English-Chinese Bi-Directional OOV Translation based on Web Mining and Supervised Learning

ACL ID P09-2033
Title English-Chinese Bi-Directional OOV Translation based on Web Mining and Supervised Learning
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

In Cross-Language Information Retrieval (CLIR), Out-of-Vocabulary (OOV) detection and translation pair relevance evaluation still remain as key problems. In this paper, an Eng- lish-Chinese Bi-Directional OOV translation model is presented, which utilizes Web mining as the corpus source to collect translation pairs and combines supervised learning to evaluate their association degree. The experimental re- sults show that the proposed model can suc- cessfully filter the most possible translation candidate with the lower computational cost, and improve the OOV translation ranking ef- fect, especially for popular new words.