Using domain-specific and collaborative resources for term translation

In this article we investigate the translation of terms from English into German and vice versa in the isolation of an ontology vocabulary. For this study we built new domainspecific resources from the translation search engine Linguee and from the online encyclopedia Wikipedia. We learned that a domainspecific resource produces better results than a bigger, but more general one. The first finding of our research is that the vocabulary and the structure of the parallel corpus are important. By integrating the multilingual knowledge base Wikipedia, we further improved the translation wrt. the domain-specific resources, whereby some translation evaluation metrics outperformed the results of Google Translate. This finding leads us to the conclusion that a hybrid translation system, a combination of bilingual terminological resources and statistical machine translation can help to improve translation of domain-specific terms.This work has been funded under the Seventh Framework Programme for Research and Technological Development of the European Commission through the T4ME contract (grant agreement no.: 249119) and in part by the European Union under Grant No. 248458 for the Monnet project as well as by the Science Foundation Ireland under Grant No. SFI/08/CE/I1380 (Lion-2). The authors would like to thank Susan-Marie Thomas, Tobias Wunner, Nitish Aggarwal and Derek De Brandt for their help with the manual evaluation. We are grateful to the anonymous reviewers for their valuable feedbac