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Does dictionary based bilingual retrieval work in a non-normalized index?

机译：基于字典的双语检索是否可以在非规范索引中工作？

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摘要

Many operational IR indexes are non-normalized, i.e. no lemmatization or stemming techniques, etc. have been employed in indexing. This poses a challenge for dictionary-based cross-language retrieval (CLIR), because translations are mostly lemmas. In this study, we face the challenge of dictionary-based CLIR in a non-normalized index. We test two optional approaches: FCG (Frequent Case Generation) and s-gramming. The idea of FCG is to automatically generate the most frequent inflected forms for a given lemma. FCG has been tested in monolingual retrieval and has been shown to be a good method for inflected retrieval, especially for highly inflected languages. S-gramming is an approximate string matching technique (an extension of n-gramming). The language pairs in our tests were English-Finnish, English-Swedish, Swedish-Finnish and Finnish-Swedish. Both our approaches performed quite well, but the results varied depending on the language pair. S-gramming and FCG performed quite equally in all the other language pairs except Finnish-Swedish, where s-gramming outperformed FCG.
机译：许多可操作的IR索引未经标准化，即在索引编制过程中未采用词条化或词干提取技术等。这对基于字典的跨语言检索（CLIR）构成了挑战，因为翻译主要是引理。在这项研究中，我们在非规范化索引中面临基于字典的CLIR的挑战。我们测试了两种可选方法：FCG（常见案例生成）和s-gramming。 FCG的想法是针对给定引理自动生成最常见的变形形式。 FCG已在单语检索中进行了测试，并且已被证明是一种有效的词尾检索方法，特别是对于高度词尾的语言。 S-gramming是一种近似的字符串匹配技术（n-gramming的扩展）。我们测试中的语言对为英语-芬兰语，英语-瑞典语，瑞典语-芬兰语和芬兰语-瑞典语。我们的两种方法都执行得很好，但是结果因语言对而异。除了芬兰语-瑞典语外，S-gramming和FCG在所有其他语言对中的表现均相当，其中s-gramming优于FCG。

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