PCA-BASED DIMENSIONALITY REDUCTION METHOD FOR USER INFORMATION IN UNIVERSAL NETWORK

摘要：

　　Universal Network (UN) is one kind of future lntemet architecture.The collection and analysis of user information is a core in the management system of UN.However,users high-dimensional data affects the performance greatly because it brings in a long response delay when matching user information with strategy rules.An efficient dimensionality reduction method is important to improve the matching efficiency on high-dimensional data.This paper introduces a statistic computational method based on Principal Component Analysis (PCA) for the reduction of user information.The method converts multiple indicators into fewer overall indicators by taking the advantage of the relations among attributes.Then,we apply this algorithm in the user information management system of UN and make several experiments to evaluate and analyze its performance.Experimental results show that the time of querying and matching is reduced by the proposed method on the condition of not losing much information of original attributes.It proves that this method reduces the dimension effectively and can be applied in the high-dimensionality user information management system.

关键词： PCA-based dimensionality reduction user information Universal Network

作者: Yu Dai Jianfeng Guan Wei Quan Changqiao Xu Hongke Zhang

作者单位: State Key Laboratory of Networking and Switching Technology,Beijing University of Post and Telecommu State Key Laboratory of Networking and Switching Technology,Beijing University of Post and Telecommu State Key Laboratory of Networking and Switching Technology,Beijing University of Post and Telecommu

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 93-97

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）