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Dictionary-based techniques for cross-language information retrieval

机译：基于字典的跨语言信息检索技术

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Cross-language information retrieval (CLIR) systems allow users to find documents written in different languages 14 from that of their query. Simple knowledge structures such as bilingual term lists have proven to be a remarkably useful basis for bridging that language gap. A broad array of dictionary-based techniques have demonstrated utility, but comparison across techniques has been difficult because evaluation results often span only a limited range of conditions. This article identifies the key issues in dictionary-based CLIR, develops unified frameworks for term selection and term translation that help to explain the relationships among existing techniques, and illustrates the effect of those techniques using four contrasting languages for systematic experiments with a uniform query translation architecture. Key results include identification of a previously unseen dependence of pre- and post-translation expansion on orthographic cognates and development of a query-specific measure for translation fanout that helps to explain the utility of structured query methods. (C) 2004 Elsevier Ltd. All rights reserved.
机译：跨语言信息检索（CLIR）系统允许用户查找以与查询语言不同的语言编写的文档14。事实证明，诸如双语术语列表之类的简单知识结构是弥合这种语言鸿沟的非常有用的基础。各种各样的基于字典的技术已显示出实用性，但是由于评估结果通常仅在有限的条件范围内，因此跨技术进行比较一直很困难。本文确定了基于字典的CLIR中的关键问题，开发了用于术语选择和术语翻译的统一框架，有助于解释现有技术之间的关系，并说明了使用四种对比语言进行统一查询翻译的系统实验使用这些技术的效果。建筑。关键结果包括识别翻译前和翻译后扩展之前对拼字法认知的依赖性，以及开发针对翻译扇出的查询专用量度，以帮助解释结构化查询方法的实用性。 （C）2004 Elsevier Ltd.保留所有权利。

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