基于位置和余弦的字符串相似度计算

Na Cheng, Zhongqing Yu, Kaixi Wang
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引用次数: 4

摘要

电子商务平台需要根据产品的特性和性价比进行产品选择功能,同时在生产和销售过程中需要对数据进行清理,因此计算产品之间的相似度是很重要的。本文提出了一种计算字符串相似度的新方法:将字符串分割成单词,对对应的位置进行编号,并对字符串进行矢量化。然后通过计算两个向量的余弦角来计算字符串之间的相似性。实验表明,该方法避免了LCS和GST的最大值或最小值。此外,该方法还提高了相似度计算的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
String similarity computing based on position and cosine
E-Business platform needs to have the production selection functionalities according to the products' feature and their cost performance, and at the same time, we need to clean data in the production and sale process, so it is important to calculate similarity between products. This paper proposes a new way to compute the similarity of string by segmenting string into words, numbering the corresponding positions and vectorizing the string. Then the similarity between the strings is computed by computing the cosine angle of the two vectors. Experiments show that the method avoids the maximum or minimum of LCS and GST. In addition, the proposed method also improves the accuracy of similarity calculation.
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