A Matching Technique in Example-Based Machine Translation
<|reference_start|>A Matching Technique in Example-Based Machine Translation: This paper addresses an important problem in Example-Based Machine Translation (EBMT), namely how to measure similarity between a sentence fragment and a set of stored examples. A new method is proposed that measures similarity according to both surface structure and content. A second contribution is the use of clustering to make retrieval of the best matching example from the database more efficient. Results on a large number of test cases from the CELEX database are presented.<|reference_end|>
@article{cranias1995a,
    title={A Matching Technique in Example-Based Machine Translation},
    author={Lambros Cranias, Harris Papageorgiou, Stelios Piperidis (Institute for
  Language and Speech Processing, Greece)},
    journal={arXiv preprint arXiv:cmp-lg/9508005},
    year={1995},
    archivePrefix={arXiv},
    eprint={cmp-lg/9508005},
    primaryClass={cmp-lg cs.CL}
}