%0 Journal Article
%T A Discriminative Reranking Approach to Spelling Correction<br>一种基于判别式重排序的拼写校正方法
%A ZHANG Yang
%A HE Pi-Lian
%A XIANG Wei
%A LI Mu
%A <br>张扬
%A 何丕廉
%A 向伟
%A 李沐
%J 软件学报
%D 2008
%I 
%X This paper proposes an approach to spelling correction. It reranks the output of an existing spelling corrector, Aspell. A discriminative model (Ranking SVM) is employed to improve upon the initial ranking, using additional features as evidence. These features are derived from state-of-the-art techniques in spelling correction, including edit distance, letter-based n-gram, phonetic similarity and noisy channel model. This paper also presents a method to automatically extract training samples from the query log chain. The system outperforms the baseline Aspell greatly, as well as the previous models and several off-the-shelf systems (e.g. spelling corrector in Microsoft Word 2003). The experimental results based on query chain pairs are comparable to that based on manually-annotated pairs, with 32.2%/32.6% reduction in error rate, respectively.
%K spelling correction
%K discriminative model
%K reranking
%K log mining
%K query chain<br>拼写校正
%K 判别模型
%K 重排序
%K 日志挖掘
%K 查询链
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=9926D1D7AE0CC7FDD71A745B0E38A82A&yid=67289AFF6305E306&vid=2A8D03AD8076A2E3&iid=38B194292C032A66&sid=2E15A588990CC690&eid=2497388423811B81&journal_id=1000-9825&journal_name=软件学报&referenced_num=0&reference_num=32