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Cross-Language High Similarity Search Using a Conceptual Thesaurus

机译:使用概念词库的跨语言高相似度搜索

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This work addresses the issue of cross-language high similarity and near-duplicates search, where, for the given document, a highly similar one is to be identified from a large cross-language collection of documents. We propose a concept-based similarity model for the problem which is very light in computation and memory. We evaluate the model on three corpora of different nature and two language pairs English-German and English-Spanish using the Eurovoc conceptual thesaurus. Our model is compared with two state-of-the-art models and we find, though the proposed model is very generic, it produces competitive results and is significantly stable and consistent across the corpora.
机译:这项工作解决了跨语言高度相似和近重复搜索的问题,对于给定的文档,要从大量的跨语言文档集中识别出高度相似的搜索。针对该问题,我们提出了一个基于概念的相似性模型,该模型在计算和存储方面非常轻便。我们使用Eurovoc概念词库评估了三个不同性质的语料库和两个语言对的英语-德语和英语-西班牙语对模型的评估。我们的模型与两个最新模型进行了比较,我们发现,尽管所提出的模型非常通用,但它产生了竞争性结果,并且在整个语料库中具有显着的稳定性和一致性。

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