Paper: Fusion of Multiple Features and Ranking SVM for Web-based English-Chinese OOV Term Translation

ACL ID C10-2164
Title Fusion of Multiple Features and Ranking SVM for Web-based English-Chinese OOV Term Translation
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

This paper focuses on the Web-based English-Chinese OOV term translation pattern, and emphasizes particularly on the translation selection strategy based on the fusion of multiple features and the ranking mechanism based on Rank- ing Support Vector Machine (Ranking SVM). By utilizing the CoNLL2003 corpus for the English Named Entity Recognition (NER) task and selected new terms, the experiments based on different data sources show the consis- tent results. Our OOV term translation model can “filter” the most possible translation candidates with better abili- ty. From the experimental results for combining our OOV term translation model with English-Chinese Cross- Language Information Retrieval (CLIR) on the data sets of Text Retrieval Eval- uation Conference (TREC), it ...