A multilingual text mining approach to web cross-lingual text retrieval

被引:15
作者
Chau, RW [1 ]
Yeh, CH [1 ]
机构
[1] Monash Univ, Fac Informat Technol, Sch Business Syst, Clayton, Vic 3800, Australia
关键词
multilingual text mining; cross-lingual text retrieval; agent; fuzzy clustering; fuzzy classification;
D O I
10.1016/j.knosys.2004.04.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To enable concept-based cross-lingual text retrieval (CLTR) using multilingual text mining, our approach will first discover the multilingual concept-term relationships from linguistically diverse textual data relevant to a domain. Second, the multilingual concept-term relationships, in turn, are used to discover the conceptual content of the multilingual text, which is either a document containing potentially relevant information or a query expressing an information need. When language-independent concepts hidden beneath both document and query are revealed, concept-based matching is made possible. Hence, concept-based CLTR is facilitated. This approach is employed for developing a multi-agent system to facilitate concept-based CLTR on the Web. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:219 / 227
页数:9
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