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A Method of Calculating Comment Text Similarity Based on Tree Structure

机译:基于树形结构的评论文本相似度计算方法

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Text similarity measure has a significance role in promoting the development of information processing. To address the comment text, this paper proposes a method, which is based on tree structure, of measuring text contents similarity. Taking advantage of comment text's content organization features to transform full text into a tree structure, this method divides the similarity measure of comment texts into that of the corresponding parts between the layers of trees. Accordingly the objects of similarity measure in each layer are the same type of words. Then suitable methods of similarity measure are adopted respectively, and different weights are given to the similarities in different layers. Finally, the overall similarity is achieved by combining the similarities in all the different tree layers. The experimental results on Amazon datasets show that the proposed method is more effective and has a higher accuracy than other common measuring methods.
机译:文本相似性度量在促进信息处理的发展中具有重要作用。针对评论文本,本文提出了一种基于树结构的文本内容相似度测量方法。利用注释文本的内容组织功能将全文转换为树形结构,该方法将注释文本的相似性度量划分为树层之间相应部分的相似性度量。因此,每一层中的相似性度量的对象是相同类型的单词。然后分别采用合适的相似度度量方法,并对不同层次的相似度赋予不同的权重。最后,通过组合所有不同树层中的相似度来实现整体相似度。在Amazon数据集上的实验结果表明,与其他常用的测量方法相比,该方法更有效且具有更高的准确性。

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