基于多策略的维吾尔文网页识别方法

An Approach to Uyghur Webpage Recognition Based on Multi-strategy

经过对大量维吾尔文网站的调查与分析,该文从多语种混合网页中针对维吾尔文网页识别进行了研究,这对维吾尔语信息处理工作起着关键作用。首先该文探讨了维吾尔文不规范网页的字符编码转换规则及原理,以此对不规范维吾尔文字符进行了相应的处理,之后介绍了基于修改的N-Gram方法和基于维吾尔语常用词特征向量的两种方法,其中后者融合了维吾尔文常用候选词语料库及向量空间模型(Vector Space Model)。使用三种不同类型的维吾尔文网页文本作为本研究的数据集,在此基础上验证了该文提出的网页识别方法,以及采用不同的方法进行了网页识别的实验。实验结果表明,基于N-Gram的方法对正文较长的新闻或论坛网页的识别性能最佳,反而基于常用词特征向量的方法对短文本的网页识别性能优越N-Gram。所提方法对维吾尔文网页识别的整体性能达到90%以上,并验证了这两种方法的有效性。

This paper studies the web-page identification task for Uyghur. It first develops the the character encoding conversion rules for non-standard Uyghur characters in the webpages. Then, two identification approaches are described： one is the modified N-Gram method （MNG） method and the other is that a feature vector method （utilizing the frequent Uyghur words via an VSM ）. The experimental datasets constitute of three different types of Uyghur web-pages. The results show that N-Gram based approach performs better in identifying web-pages with long texts as in news site and forum, while the feature vector approach out-performes in web-pages of short text. Combining these two methods yields above 90% F1 score in the experiment.