曾伟
近期热点
资料介绍
个人简历
个人背景本人一共发表学术论文14篇,以第一作者发表学术论文10篇,其中6篇SCI检索论文,论文发表期刊影响因子最高5.578,总的影响因子20.72。科研方向擅长于算法设计、数值分析和建模。多次到香港、海外知名高校访问,例如香港浸会大学、华沙大学、瑞士弗里堡大学、罗马大学。一共主持了两项国际项目和一项国家自然科学基金项目:OnthediversityProblemofRecommenderSystems(EG57-092011)、SinoSwissScienceandTechnologyCooperationProgramFollow-upGrants(TE-70382)和推荐系统的信息核挖掘及其应用研究(61502078),作为主研参与了多项国家科学自然基金项目。目前从事的工作主要包括:个性化推荐、国家GDP预测、大数据金融。金融大数据的研究内容包括金融产品个性化营销和金融风险预测预警,目前已服务于中国银行、建设银行、民生银行和成都银行等多家金融机构。研究项目1.OnthediversityProblemofRecommenderSystems(EG57-092011),瑞士联邦政,2012–2013。2.SinoSwissScienceandTechnologyCooperationProgramFollow-upGrants(TE-70382),瑞士联邦政府,2014.7–2014.9。3.推荐系统的信息核挖掘及其应用研究(61502078),国家科学自然基金,2016-2018。4.大数据金融,民生银行,主持,2014-20155.个性化营销,中行四川省分行,主持,2016-20176.风险预警,成都银行,主持,2015-2016论文列表研究领域
长期从事推荐系统的研究工作,研究内容包括:推荐系统多样性、数据稀疏性和推荐网络结构分析。近期论文
[1]WeiZeng,AnZeng,HaoLiu,Ming-shengShangandTaoZhou,Uncoveringtheinformationcoreinrecommendersystems,ScientificReport4:6140.(SCI,IF=5.578,AN6OO)[2]WeiZeng,AnZeng,Ming-shengShang,Yi-chengZhang,Informationfilteringinsparseonlinesystems:recommendationviasemi-localdiffusion,PLoSONE8:e79354.(SCI,IF=3.52,256KH)[3]WeiZeng,AnZeng,HaoLiu,Ming-shengShangandYi-chengZhang,Similarityfrommulti-dimensionalscaling:solvingtheaccuracyanddiversitydilemmaininformationfiltering,PLoSONE.(SCI,IF=3.52)[4]WeiZeng,YuxiaoZhu,LinyuanLüandTaoZhou,Negativeratingsplayapositiveroleininformationfiltering,PhysicaA,390:4486-4493(SCI,IF=1.722,829RP)[5]WeiZeng,AnZeng,Ming-shengShangandYi-chengZhang,Membershipinsocialnetworksandtheapplicationininformationfiltering,TheEuropeanPhysicalJournalB,86:375.(SCI,IF=1.483,226EJ)[6]WeiZeng,Ming-ShengShang,Qian-MingZhang,LinYuanLü,TaoZhou,Candissimilaruserscontributetoaccuracyanddiversityofpersonalizedrecommendation?InternationalJournalofModernPhysicsC(IJMPC),2010,21:1217-1227(SCI,IF=1.125)[7]WeiZengandLiChen,HeterogeneousDataFusionviaMatrixFactorizationforAugmentingItem,GroupandFriendRecommendations,The28thACMSymposiumOnAppliedComputing,SAC2013,Coimbra,Portugal,March18-22,2013.(EI检索)[8]WeiZengandLiChen.RecommendingInterestGroupstoSocialMediaUsersbyIncorporatingHeterogeneousResources.InProceedingsof26thInternationalConferenceonIndustrial,Engineering&OtherApplicationsofAppliedIntelligentSystems(IEA/AIE’13),pages361-371,Amsterdam,Netherlands,June17-21,2013.(EI检索)[9]LiChenandWeiZengandQuanYuan,Aunifiedframeworkforrecommendingitems,groupsandfriendsinsocialmediaenvironmentviamutualresourcefusion,ExpertSyst.Appl.40:2889-2903.(SCI,IF=1.965,111LN)[10]Ming-ShengShang,LinYuanLü,WeiZeng,TaoZhouandYi-ChengZhang,Relevanceismoresignificantthancorrelation:Informationfilteringonsparsedata.EurophysicsLetters,2009,88:68008(SCI,IF=2.269)[11]WeiZeng,Ming-ShengShang,Tie-YunQian,Usefulacquiringratingsforcollaborativefiltering.2009IEEEYouthConferenceonInformationComputingandTelecommunication(YC-ICT'09),483.(EI检索)[12]WeiZengandMing-ShengShang,Effectsofnegativeratingsonpersonalizedrecommendation.20105thInternationalConferenceonComputerScienceandEducation(ICCSE),375(EI检索)[13]Yu-XiaoZhu,WeiZengandQian-MingZhang,Theeffectofratingvarianceonpersonalizedrecommendation,20105thInternationalConferenceonComputerScienceandEducation(ICCSE),366(EI检索)[14]Qian-MingZhang,Ming-ShengShang,WeiZeng,YongChenandLinyuanLü,Empiricalcomparisonoflocalstructuralsimilarityindicesforcollaborative-filtering-basedrecommendersystems,PhysicsProcedia,2010,3:1887-1896(EI检索)标签: 计算机科学与工程学院 电子科技大学
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