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A new document representation using term frequency and vectorized graph connectionists with application to document retrieval

机译:使用术语频率和矢量化图连接器的新文档表示形式及其在文档检索中的应用

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This paper presents a new document representation with vectorized multiple features including term frequency and term-connection-frequency. A document is represented by undirected and directed graph, respectively. Then terms and vectorized graph connectionists are extracted from the graphs by employing several feature extraction methods. This hybrid document feature representation more accurately reflects the underlying semantics that are difficult to achieve from the currently used term histograms, and it facilitates the matching of complex graph. In application level, we develop a document retrieval system based on self-organizing map (SOM) to speed up the retrieval process. We perform extensive experimental verification, and the results suggest that the proposed method is computationally efficient and accurate for document retrieval.
机译:本文提出了一种具有矢量化多个特征的新文档表示形式,包括术语频率和术语连接频率。文档分别由无向图和有向图表示。然后,通过采用几种特征提取方法从图中提取项和矢量化的图形连接论者。此混合文档特征表示可更准确地反映从当前使用的术语直方图难以实现的底层语义,并且有助于复杂图的匹配。在应用程序级别,我们开发了一种基于自组织图(SOM)的文档检索系统,以加快检索过程。我们进行了广泛的实验验证,结果表明,该方法在计算效率和准确度上都可用于文档检索。

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