Automatic Construction of Chinese-Mongolian Parallel Corpora from the Web Based on the New Heuristic Information

Zede Zhu, Miao Li, Lei Chen, Shouguo Zheng
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引用次数: 2

Abstract

Parallel corpora are important resources in data-driven natural language processing domain. Concerning the issues such as the scale, comprehensiveness and timeliness, the existing Chinese-Mongolian parallel corpora are significantly limited in practical use. Reviewing the traditional heuristic information used to identify major languages parallel web pages, this paper focuses on exploring new heuristic information to improve the performance of identifying Chinese-Mongolian parallel pages. Based on these heuristics, support vector machine is used to classify webs as parallel pages or non-parallel pages. Experiment gains a precision rate of 95% and a recall rate of 88%. This paper makes preliminary research in automatically constructing minority languages parallel corpora from the web.
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基于新启发式信息的网络汉蒙平行语料库自动构建
并行语料库是数据驱动的自然语言处理领域的重要资源。现有的汉蒙平行语料库在规模、全面性、时效性等方面存在较大的局限性。本文在回顾传统的主要语言平行网页识别启发式信息的基础上,重点探索新的启发式信息,以提高汉蒙平行网页的识别性能。基于这些启发式方法,使用支持向量机将网页分类为并行页面或非并行页面。实验获得了95%的准确率和88%的召回率。本文对基于网络的少数民族语言并行语料库的自动构建进行了初步研究。
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