二度人脉聚类算法设计  

Design of 2nd contacts clustering algorithm

作　　者：张保龙[1] 黄海燕[1] 

机构地区：[1]郑州科技学院,河南郑州450064

出　　处：《现代电子技术》2016年第9期126-127,132,共3页Modern Electronics Technique

摘　　要：针对整个复杂CLASS全属性聚类的聚类算法在聚类算法中有较为复杂的实现要求,试图对社交软件中较为复杂的CLASS-USER进行整体聚类计算,难度在于将其复杂属性体系整合成高维度变量进行降维处理。通过多次连续的数据整理,特别使用了二维模糊矩阵与排序算法实现快速降维,将高达13维的高维度变量进行降维处理,最终形成一维变量,最后使用常见的K-means聚类算法对该一维变量进行聚类分析。Since the whole complex CLASS full-attribute clustering algorithm in clustering algorithms has complicated implementation requirement,the overall clustering computation for the more complex CLASS-USER in social software is tried to carry out,which is difficult to integrate the complex attribute system into the high dimensional variables for dimension reduction processing. The ranking algorithm of two-dimensional fuzzy matrix is particularly used to fast reduce the dimension by means of repeatedly continuous data processing. The dimension reduction processing for the high dimensional variables with 13 dimensions is conducted to form the one-dimensional variable. And then the cluster analysis for the one-dimensional variable is conducted with common K-means clustering algorithm.

关 键 词：全属性聚类 社交软件 聚类算法 人脉分析 

分 类 号：TN911-34[电子电信—通信与信息系统]