首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于互近邻一致性的近邻传播算法
引用本文:邢 艳,周 勇.基于互近邻一致性的近邻传播算法[J].计算机应用研究,2012,29(7):2524-2526.
作者姓名:邢 艳  周 勇
作者单位:中国矿业大学计算机学院,江苏徐州,221116
基金项目:国家教育部博士点基金资助项目(20100095110003); 国家博士后科学基金资助项目(20070421041); 江苏省博士后科学基金资助项目(0701045B); 中国矿业大学科技基金资助项目(2007B017)
摘    要:近邻传播(AP)算法是一种新提出的聚类算法,是在数据点的相似度矩阵的基础上进行聚类,通过数据点之间交换信息,最后得到聚类结果。提出了基于互近邻一致性近邻传播算法,即KMNC-AP算法,该算法利用互近邻一致性调整数据点之间的相似度,进而提高聚类效率和精确度。实验结果表明,该算法在处理能力和运算速度上优于原算法。

关 键 词:近邻传播算法  互近邻一致性  相似度  数据挖掘

Affinity propagation based on K-mutual nearest neighbor consistency
XING Yan,ZHOU Yong.Affinity propagation based on K-mutual nearest neighbor consistency[J].Application Research of Computers,2012,29(7):2524-2526.
Authors:XING Yan  ZHOU Yong
Institution:School of Computer Science & Technology, China University of Mining & Technology, Xuzhou Jiangsu 221116, China
Abstract:Affinity propagation is a new clustering method. It based on the similarity between pairs of data points, through the exchange of information between data points, and finally obtained the final clustering results. This paper presented an improved AP clustering based on K-mutual nearest neighbor consistency KMNC-AP. The improved algorithm used the idea of K-mutual nearest neighbor consistency to adjust the similarity between data points. Experiments show that the improved algorithm is more accurate and faster than the original algorithm.
Keywords:affinity propagation(AP) algorithm  K-mutual nearest neighbor consistency  similarity  data mining
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《计算机应用研究》浏览原始摘要信息
点击此处可从《计算机应用研究》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号