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Bilingual topic taxonomy generation based on bilingual documents clustering

机译:基于双语文档聚类的双语主题分类法生成

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Bilingual taxonomy is one of key components of multilingual Ontology. In this paper, affinity propagation clustering algorithm is used to cluster bilingual documents collection and generate bilingual topic taxonomy. Two bilingual topic taxonomy generation methods, i.e. bilingual documents clustering before or after text feature reconstruction, are described. Dataset in two domains are tested and result shows that: according to net similarity, the result of documents clustering after feature reconstruction is better than that before feature reconstruction.
机译:双语分类法是多语言本体论的关键组成部分之一。本文采用亲和力传播聚类算法对双语文献的收集进行聚类并生成双语主题分类法。描述了两种双语主题分类法生成方法,即,在文本特征重构之前或之后的双语文档聚类。对两个领域的数据集进行了测试,结果表明:根据网络相似度,特征重构后的文档聚类结果优于特征重构前的文档聚类结果。

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