个人信息Personal Information
教授
硕士生导师
性别:男
毕业院校:吉林大学
学位:博士
所在单位:信息管理与信息系统研究所
学科:信息管理与电子政务
办公地点:管理楼518
电子邮箱:ywang@dlut.edu.cn
Customer segmentation of port based on the multi-instance kernel K-aggregate clustering algorithm
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论文类型:会议论文
发表时间:2007-08-20
收录刊物:EI
页面范围:210-215
摘要:The analyses of the port data show us that the traditional data lay-out and the exited clustering algorithms could not be used in the port customer segmentation, so this thesis presents a new three-level data bag by combined with the way inwhich the multi-instance learning treat the data. Then a multi-instance kernel function is constructed according to the new bag. When the distance between two mixed valued vectors is counted the information gains are imported to weight the different attributes. The partition coefficient and average fuzzy entropy are calculated to decide the best cluster number of the clustering algorithm. Finally the kernel k-aggregate clustering algorithm using the multi-instance kernel is applied to the customer segmentation and gets a good clustering result which provides the managers guidance and evidence of different marketing strategies for corresponding subdivided markets.