基于Web数据的特定领域双语词典抽取

Bilingual Dictionary Extraction for Special Domain Based on Web Data

双语词典是跨语言检索以及机器翻译等自然语言处理应用的基础资源。本文提出了一种从非平行语料中抽取特定领域双语词典的算法。首先给出了算法的基本假设并回顾了相关的研究方法,然后详细给出了利用词间关系矩阵法从特定领域非平行语料中抽取双语词典的过程,最后通过大量实验分析了种子词选择对词典抽取结果的影响,实验结果表明种子词的数量和频率对词典抽取结果有积极作用。

Bilingual dictionary is the base of many NLP applications such as multi-lingual information retrieval and machine translation. This paper proposes a method of extracting bilingual dictionary for the special domain from the non-parallel corpora： first, discusses the fundamental postulate and reviews the related research, second, presents an algorithm of extracting the bilingual dictionary for the special domain based on the non-parallel corpora with the word relation matrix, and finally, analyzes the influence of the seed word on the extraction of the bilingual dictionary with abundant of experimentation. The experiments demonstrate that the quantity and average frequency of the seed word pairs contribute to the results effectively.