Transliterated Word Identification and Application to Query Translation Mining  

作　　者：Jing Zhang Lei Guo Meiling Zhou Jianmin Yao 

机构地区：[1]不详

出　　处：《Journal of Software Engineering and Applications》2009年第2期122-126,共5页软件工程与应用（英文）

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.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 

分 类 号：R73[医药卫生—肿瘤]