Bilingual corpus is one of the most important parts in translation memory system.
双语库是翻译记忆系统最重要的组成部分之一。
Building a large scale of bilingual corpus is the foundation of research on corpus.
大规模双语语料库的建设是进行基于语料库研究的基础。
Align bilingual corpus is a natural language processing important research subject.
双语语料对齐是自然语言处理的一个重要研究课题。
This paper develops a platform of Chinese-English bilingual corpus for Chinese medicine.
构建中医汉英双语语料库平台并介绍其主要功能。
Bilingual Corpus alignment of natural language processing is an important research topic.
双语语料库自动对齐是自然语言处理的一个重要研究课题。
Aligning the bilingual corpus at word level is very important to take the advantages of corpus.
语料库词汇一级的对齐，对于充分发挥语料库的作用意义重大。
Third, we have conducted the research to the acquisition of bilingual chunk on bilingual corpus.
第三，在双语语料库的基础上进行了双语组块获取的研究。
To support an ongoing Chinese-English machine translation project, a Chinese English bilingual corpus is being set up.
为了支持一项正在进行的汉英机器翻译系统的开发，我们建立了一个汉英双语语料库。
Large amount of bilingual resource on the Internet bring the probability of building a large scale of bilingual corpus.
网络上存在的大量双语资源，给构建大规模双语语料库提供了可能。
How to use the existing bilingual text to build the large scale of bilingual corpus made it important to process the bilingual text.
如何通过现有的互译文本来建立大规模的双语语料库，对双语互译文本的加工成为至关重要的问题。
The system needs a large and high-quality Bilingual Corpus. To build such a Corpus, one of the key technologies is Bilingual Sentence Alignment.
该系统中需要一个大规模、高质量的双语语料库，而要建设这样一个双语库，其中的关键技术就是双语句子对齐。
Bilingual corpus plays an important role in Example-base Machine translation (EBMT), acquirement of translation knowledge, construction of bilingual dictionary etc.
双语语料库在基于实例的机器翻译、翻译知识的获取、双语词典的建立、词义消歧等领域有着重要的应用价值。
An alignment method which makes use of thesaurus and bilingual corpus is adopted and thus the number of Chinese translation of word in English Chinese dictionaries is enlarged.
采用《汉语同义词词林》和英汉双语语料库，通过“双语对齐”扩充了英汉词典的单词译文；
The word translation probability was calculated by 4 common co-occurrence models in bilingual corpus, and the translation equivalence was extracted according to translation probability.
基于双语语料库可自动抽取翻译等价对：利用4种常见的数学模型来计算任意两个词的共现频率，以共现频率的高低来获取翻译等价对。
Word alignment is a basic problem of Cross-lingual Natural Language Processing. Many NLP tasks based on bilingual corpus such as SBMT, EBMT, WSD, Automated Dictionary Extraction need to align words.
词语对齐是跨语言自然语言处理领域的一个基本问题，许多基于双语语料库的应用(如sbmt、EBMT、WSD、词典编纂)都需要词汇级别的对齐。
The method first constructs a paraphrase corpus by automatically translating a bilingual parallel corpus into a monolingual parallel corpus, from which candidate paraphrases for words are extracted.
该方法首先利用翻译引擎将双语平行语料库自动转换为单语平行语料库，以此构建复述语料库并用于候选复述的抽取。
Moreover , the parallel corpus is valuable in machine translation , bilingual dictionary compilation , word sense disambiguation and cross - lingual information retrieval.
除机器翻译方面的应用之外，平行语料库的建设对于双语词典编纂、词义消岐和跨语言信息检索也具有重要价值。
Parallel corpus has valuable application in machine translation, bilingual dictionary compilation, word sense disambiguation and Cross-Lingual Information Retrieval.
除机器翻译方面的应用之外，平行语料库的建设对于双语词典编纂、词义消岐和跨语言信息检索也具有重要价值。
As the key technology during the course of building the corpus, Bilingual alignment technology is growing High recognition.
双语对齐作为语料库加工过程中的关键技术，已经引起研究者的高度重视。
This dissertation presents a method on extracting bilingual translation tuples from a comparable corpus.
本文提出的从大规模网页中抽取双语翻译对的方法是基于可比较语料的。
However, access to a large-scale bilingual parallel corpus is not easy, the existing parallel corpora can not meet the actual needs in terms of the scale, timeliness and balance of the fields.
但是大规模双语平行语料库的获取并不容易，现有的平行语料库在规模、时效性和领域的平衡性等方面还不能满足处理真实文本的实际需要。
However, access to a large-scale bilingual parallel corpus is not easy, the existing parallel corpora can not meet the actual needs in terms of the scale, timeliness and balance of the fields.
但是大规模双语平行语料库的获取并不容易，现有的平行语料库在规模、时效性和领域的平衡性等方面还不能满足处理真实文本的实际需要。
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