非均衡IPTV数据集下的用户报障预测  

Prediction for User's Complaint in Imbalanced IPTV Dataset

作　　者：吴志峰 黄若尘 魏昕[1] 黄荣谞 周亮[1] Wu Zhifeng;Huang Ruochen;Wei Xin;Huang Rongxu;Zhou Liang(College of Telecommunication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing,210003,China;China Telecommunications Jiangsu Branch,Nanjing,210017,China)

机构地区：[1]南京邮电大学通信与信息工程学院,南京210003 [2]中国电信江苏分公司,南京210017

出　　处：《数据采集与处理》2018年第1期75-84,共10页Journal of Data Acquisition and Processing

基　　金：国家重点基础研究发展计划(2013CB329005)资助项目;国家自然科学基金(61322104;61571240)资助项目;江苏高校优势学科建设工程资助项目;江苏省自然科学基金(BK20161517)资助项目;江苏省青蓝工程资助项目

摘　　要：针对传统算法在非均衡交互式网络电视(Internet protocol television,IPTV)数据集下用户报障预测效果不理想的问题,本文将影响网络服务质量(Quality of service,Qo S)的传统网络参数和主观反映用户体验质量(Quality of experience,Qo E)的MOS评分结合来预测用户是否报障。本文在已有的ODRBSMOTE-SVM算法基础上,针对过采样算法产生噪声以及核参数没有进行优化的缺陷,提出了一种改进型算法。该改进算法首先采用欠采样、过采样算法及数据清洗算法对原始非均衡数据进行处理,然后通过自适应变核参数寻找近似最优值,最终实现提升分类效果。实验结果表明,较传统标准支持向量机(Support vector machine,SVM)算法和ODR-BSMOTE-SVM算法,本文算法能获得更佳的预测效果。In the imbalanced internet protocol television(IPTV)dataset,the traditional algorithm performs not well in terms of predicting the user′s complaint.For this problem,this paper combines traditional network parameters that influence the network quality of service(QoS)with MOS score that objectively reflects the quality of experience(QoE)to predict user′s complaint.And then we propose an improved algorithm based on the existing ODR-BSMOTE-SVM algorithm for the defects that the over sampling algorithm will produce noise and there is not any optimization for kernel parameters.In the improved algorithm,under sampling algorithm,over sampling algorithm and data cleaning algorithm are firstly used to process the original imbalanced dataset.Then,through searching for the approximate optimal value by adaptive variable kernel parameters,the classification effect is ultimately improved.Experimental results show that the improved algorithm performs better than the traditional standard support vector machine(SVM)and the ODR-BSMOTE-SVM algorithm in predicting user′s complaint.

关 键 词：非均衡数据 服务质量 数据清洗 支持向量机 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]