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A New Document Representation Using a Unified Graph to Document Similarity Search

机译:使用统一图形到记录相似性搜索的新文档表示

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Document similarity search is to retrieve a ranked list of similar documents and find documents similar to a query document in a text corpus or a web page on the web. But most of the previous researches regarding searching for similar documents are focused on classifying documents based on the contents of documents. To solve this problem, we propose a novel retrieval approach based on undirected graphs to represent each document in corpus. In addition, this study also considers unified graph in conjunction with multiple graphs to improve the quality of searching for similar documents. Experimental results on the Reuters-21578 data demonstrate that the proposed system has better performance and success than the traditional approach.
机译:文档相似性搜索是为了检索类似文档的排名列表,并查找类似于文本语料库中的查询文档的文档或Web上的网页。但是,关于搜索类似文档的大多数研究专注于根据文件的内容对文档进行分类。为了解决这个问题,我们提出了一种基于无向图形的新型检索方法,以表示语料库中的每个文档。此外,本研究还考虑统一的图表与多个图表结合,以提高搜索类似文档的质量。路透社-21578数据上的实验结果表明,所提出的系统具有比传统方法更好的性能和成功。

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