A Comparative Study of Online Translation Services for Cross Language Information Retrieval

被引:6
作者
Vahid, Ali Hosseinzadeh [1 ]
Arora, Piyush [1 ]
Liu, Qun [1 ]
Jones, Gareth J. F. [1 ]
机构
[1] Dublin City Univ, Sch Comp, ADAPT Ctr, CNGL, Dublin 9, Ireland
来源
WWW'15 COMPANION: PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB | 2015年
关键词
Cross language information retrieval; machine translation; variable retrieval effectiveness;
D O I
10.1145/2740908.2743008
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Technical advances and its increasing availability, mean that Machine Translation (MT) is now widely used for the translation of search queries in multilingual search tasks. A number of free-to-use high -quality online MT systems are now available and, although imperfect in their translation behaviour, are found to produce good performance in Cross Language Information Retrieval (CLIR) applications. Users of these MT systems in CLIR tasks generally assume that they all behave similarly in CLIR applications, and the choice of MT system is often made on the basis of convenience. We present a set of experiments which compare the impact of applying two of the best known online systems, Google and Bing translation, for query translation across multiple language pairs and for two very different CUR tasks. Our experiments show that the MT systems perform differently on average for different tasks and language pairs, but more significantly for different individual queries. We examine the differing translation behaviour of these tools and seek to draw conclusions in terms of their suitability for use in different settings.
引用
收藏
页码:859 / 864
页数:6
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