计算机应用研究2017，Vol.34Issue(1)：46-51,57,7.DOI:10.3969/j.issn.1001-3695.2017.01.009
基于多核系统的并行线性RankSVM算法
Efficient parallel algorithm for linear RankSVM on multi-core systems
摘要
Abstract
Many effective linear RankSVM algorithms have been studied extensively.However,if making use of any one of them to deal with the large-scale linear RankSVM,then it must be taken extremely lengthy training time.According to the anal-ysis of the existing state-of-the-art algorithm Tree-TRON,if used trust region Newton method (TRON)to train the linear RankSVM,massive Hessian-vector products and the computation of the auxiliary variables could affect the training speed signif-icantly.To efficiently accelerate these computations,this paper proposed an efficient parallel algorithm (named PRankSVM)on multi-core systems.All in all,two important issues should be well handled when designing PRankSVM on multi-core systems. First,it divided the training set into several subsets in terms of different queries.Second,it efficiently utilized the great compu-tational power of the multi-core system to improve the Hessian-vector products and the computation of the auxiliary variables. The experimental results show that PRankSVMnot only can obtain the excellent convergence speed,but also can ensure the ac-curacy in prediction,while comparing with the existing methods.关键词
排序学习/线性RankSVM模型/并行计算/多核系统Key words
learning to rank/linear RankSVM/parallel computing/multi-core system分类
信息技术与安全科学引用本文复制引用
聂慧,彭娇,金晶,李康顺..基于多核系统的并行线性RankSVM算法[J].计算机应用研究,2017,34(1):46-51,57,7.基金项目
国家自然科学基金资助项目（61673157）；广东省自然科学基金资助项目 （）
