文献类型：期刊文献

英文题名：Preference Data Mining Based on Large Data and Its Application

作者：Zhao Hai-yan[1];Li Ai-ju[1];Liu Kun[1]

第一作者：赵海燕

通讯作者：Zhao, HY[1]|[1141768632a683d657ed6]赵海燕;

机构：[1]Beijing Union Univ, Coll Appl Sci & Technol, Beijing 102200, Peoples R China

第一机构：北京联合大学应用科技学院

通讯机构：[1]Beijing Union Univ, Coll Appl Sci & Technol, Beijing 102200, Peoples R China.|[1141775]北京联合大学应用科技学院;[11417]北京联合大学;

年份：2018

卷号：21

期号：2

外文期刊名：JOURNAL OF ADVANCED OXIDATION TECHNOLOGIES

收录：;Scopus(收录号：2-s2.0-85051335218);WOS:【SCI-EXPANDED(收录号:WOS:000433154904120)】；

语种：英文

外文关键词：Large data analysis; Data mining; Association rules; Preference dynamic measurement model; clustering algorithm

摘要：This paper studies the large amount of data accumulated by consumers. First of all, on the analysis of data mining data mining based on preference; and then discusses the principle of technology; third, construct the model of user preference mining data, clustering algorithm and association algorithm k- mean purchasing model based on preference; finally, and the platform is designed to realize self purchasing. Complete the mining task with the support of the platform. Customer buying interest is divided into short-term buying interest and long-term buying interest. According to customer browsing behavior and log data, mining customer's short-term interests. Using the data in the backend server database, mining initial customer registration information, extracting long-term customer purchase interest. It is better to study data mining in database analysis, which is based on consumer preference, and the construction of dynamic classification model of consumer classification results is more practical and innovative.