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基于Web电子商务平台的食用菌产品共词聚类算法

作  者:
纪琳
单  位:
浙江经济职业技术学院商贸流通学院
关键词:
电子商务;共词聚类;相似度;密度;距离
摘  要:
针对食用菌产品电子商务平台的数据挖掘问题,采用了共词聚类算法进行主题聚类,在密度聚类算法的基础上,使用了移动非密集单元的处理方法实现了共词聚类。该算法克服了传统聚类算法裁剪造成的精度误差,提高了聚类结果的精确度,应用在电子商务平台的效果良好。
译  名:
The Clustering Algorithm of Edible Fungi Product Co-words Based on Web E-commerce Platform
作  者:
JI Lin;Zhejiang Technical Institute of Economics;
关键词:
e-commerce;;co word clustering;;similarity;;density;;distance
摘  要:
Aiming at the data mining problem of e-commerce platform for edible fungi products, we use the co word clustering algorithm to cluster the topics, and on the basis of the density clustering algorithm, we use the processing method of mobile non intensive units to achieve the co word clustering. This algorithm overcomes the precision error caused by the cutting of traditional clustering algorithm, improves the accuracy of clustering results, and has a good effect in e-commerce platform.

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