文章基本信息

标题：Transliterated Word Identification and Application to Query Translation Mining
本地全文：下载
作者：Jing Zhang ; Lei Guo ; Meiling Zhou 等
期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2009
卷号：2
期号：2
页码：122-126
DOI：10.4236/jsea.2009.22018
出版社：Scientific Research Publishing
摘要：Query translation mining is a key technique in cross-language information retrieval and machine translation knowl-edge acquisition. For better performance, the queries are classified into transliterated words and non-transliterated words based on transliterated word identification model, and are further channeled to different mining processes. This paper is a pilot study on query classification for better translation mining performance, which is based on supervised classification and linguistic heuristics. The person name identification gets a precision of over 97%. Transliterated word translation mining shows satisfactory performance.
关键词：Transliteration; Query Classification; Supervised Learning; Translation Mining