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基于DT-KSVM的业务感知算法
引用本文:董昊,曲桦,赵季红,陈梁骏,戴慧珺. 基于DT-KSVM的业务感知算法[J]. 电信科学, 2015, 31(11): 67-71. DOI: 10.11959/j.issn.1000-0801.2015227
作者姓名:董昊  曲桦  赵季红  陈梁骏  戴慧珺
作者单位:1. 西安交通大学软件学院 西安 710049;2. 西安交通大学电子与信息工程学院 西安 710049;3. 西安邮电大学通信与信息工程学院 西安 710061
基金项目:国家自然科学基金资助项目;国家高技术研究发展计划(“863”计划)基金资助项目
摘    要:提出一种新的基于DT-KSVM(decision tree kernel support vector machine,决策树支持向量机)的业务感知算法,利用ReliefF特征选择算法提取特征,提出样本间类别可分度计算方法排序不同业务感知难度,优先感知易分业务。在实际网络业务数据集上与传统一对一(one-versus-one)SVM感知方法进行对比,结果表明该方法具有较高的业务识别准确率和更好的时间性能。

关 键 词:SVM  决策树  业务感知  

Service-Aware Algorithm Based on DT-KSVM
Hao Dong,Hua Qu,Jihong Zhao,Liangjun Chen,Huijun Dai. Service-Aware Algorithm Based on DT-KSVM[J]. Telecommunications Science, 2015, 31(11): 67-71. DOI: 10.11959/j.issn.1000-0801.2015227
Authors:Hao Dong  Hua Qu  Jihong Zhao  Liangjun Chen  Huijun Dai
Affiliation:1. School of Software,Xi'an Jiaotong University,Xi'an 710049,China;2. School of Electronic & Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;3. School of Telecommunication & Information Engineering,Xi'an University of Posts & Telecommunications,Xi'an 710061,China
Abstract:A novel service-aware method based on decision tree kernel support vector machine(DT-KSVM) algorithm was proposed.A service-aware model was developed by using ReliefF algorithm to extract service characteristics,and proposing the separable degree between samples to simply the service-aware process.Through experiment comparison between this proposed model and traditional one-versus-one SVM method,it is shown that the proposed method has a better service-aware accuracy and time performance.
Keywords:support vector machine  decision tree  service-aware  
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