A multilingual text mining approach to web cross-lingual text retrieval
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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.
论文关键词:Multilingual text mining,Cross-lingual text retrieval,Agent,Fuzzy clustering,Fuzzy classification
论文评审过程:Received 26 August 2003, Accepted 6 April 2004, Available online 28 May 2004.
论文官网地址:https://doi.org/10.1016/j.knosys.2004.04.001