绑架 发表于 2025-3-26 23:44:38
EBMT in a Controlled Environmentnced TM system, a . (PL), which takes advantage of the huge, underused resources available in existing translation aids. We claim that PL and EBMT systems can provide valuable translation solutions for restricted domains, especially where controlled language restrictions are imposed. When integratedSlit-Lamp 发表于 2025-3-27 03:37:39
Formalizing Translation Memory the MSSM algorithm based on dynamic programming techniques are all introduced in order to formalize Translation Memories (TM). We show how this approach leads to a real gain in recall and precision, and allows the extension of TM towards rudimentary, yet useful Example-Based Machine Translation (EBDENT 发表于 2025-3-27 08:32:43
An Example-Based Machine Translation System Using DP-Matching Between Word Sequencesng out DP-matching of the input sentence and source sentences in an example database while measuring the semantic distances of the words. Second, the approach adjusts the gap between the input and the most similar example by using a bilingual dictionary. We demonstrate its high coverage and accuracy纪念 发表于 2025-3-27 10:29:51
http://reply.papertrans.cn/83/8228/822745/822745_34.png短程旅游 发表于 2025-3-27 16:20:39
EBMT of POS-Tagged Sentences by Recursive Division Via Inductive Learning The sentence is divided according to the structure of similar examples extracted during the matching process. The approach is especially intended for languages where resources and tools are pretty much unavailable. POS taggers are the only tools utilized, and the bilingual corpus the only resourceAMPLE 发表于 2025-3-27 18:12:11
Learning Translation Templates from Bilingual Translation Examplespondences are learned using analogical reasoning between two translation examples. Given two translation examples, any similarities in the source language sentences must correspond to the similar parts of the target language sentences, while any differences in the source strings must correspond to tPANG 发表于 2025-3-27 23:24:11
http://reply.papertrans.cn/83/8228/822745/822745_37.png加强防卫 发表于 2025-3-28 03:19:39
http://reply.papertrans.cn/83/8228/822745/822745_38.png夹克怕包裹 发表于 2025-3-28 09:29:26
http://reply.papertrans.cn/83/8228/822745/822745_39.pngintrigue 发表于 2025-3-28 11:41:00
Extracting Translation Knowledge from Parallel Corporacally probable dependency relations to acquire word and phrasal correspondences. We obtained 90% precision using an English-Japanese parallel corpus of 9268 sentences in the business domain. The result showed that statistically probable dependency relations are effective in translation knowledge acq