Translation Techniques in Cross-Language Information Retrieval

被引：42

作者：

Zhou, Dong ^{[1
,2
]}

Truran, Mark ^{[3
]}

Brailsford, Tim ^{[4
]}

Wade, Vincent ^{[2
]}

Ashman, Helen ^{[5
]}

机构：

[1] Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan, Hunan, Peoples R China

[2] Trinity Coll Dublin, Dublin, Ireland

[3] Univ Teesside, Middlesbrough, Cleveland, England

[4] Univ Nottingham, Nottingham NG7 2RD, England

[5] Univ S Australia, Adelaide, SA 5001, Australia

来源：

ACM COMPUTING SURVEYS | 2012年 / 45卷 / 01期

基金：

爱尔兰科学基金会;

关键词：

Algorithms; Languages; Cross-language information retrieval; query translation; document translation; bilingual dictionary; parallel corpora; machine translation; semantic model; TRANSITIVE DICTIONARY TRANSLATION; WEB; MODELS; QUERY; CLIR;

D O I：

10.1145/2379776.2379777

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Cross-language information retrieval (CLIR) is an active sub-domain of information retrieval (IR). Like IR, CLIR is centered on the search for documents and for information contained within those documents. Unlike IR, CLIR must reconcile queries and documents that are written in different languages. The usual solution to this mismatch involves translating the query and/or the documents before performing the search. Translation is therefore a pivotal activity for CLIR engines. Over the last 15 years, the CLIR community has developed a wide range of techniques and models supporting free text translation. This article presents an overview of those techniques, with a special emphasis on recent developments.

引用

页数：44

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