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1、ISSN1000-9825,CODENRUXUEWE-mail:jos@iscas.ac.cnJournalofSoftware,Vol.18,No.10,October2007,pp.2403−2411http://www.jos.org.cnDOI:10.1360/jos182403Tel/Fax:+86-10-62562563©2007byJournalofSoftware.Allrightsreserved.∗基于云模型的协同过滤推荐算法1,4+2312张光卫,李德毅,李鹏,康建初,陈桂生1(北京航空航天大学软件开发环境国家
2、重点实验室,北京100083)2(中国电子工程系统研究所,北京100840)3(哈尔滨工业大学深圳研究生院信息安全中心,广东深圳518055)4(山东建筑大学计算机科学与技术学院,山东济南250101)ACollaborativeFilteringRecommendationAlgorithmBasedonCloudModel1,4+2312ZHANGGuang-Wei,LIDe-Yi,LIPeng,KANGJian-Chu,CHENGui-Sheng1(StateKeyLaboratoryofSoftwareDevelopment
3、Environment,BeiHangUniversity,Beijing100083,China)2(InstituteofElectronicSystemEngineering,Beijing100840,China)3(InformationSecurityCenter,ShenzhenGraduateSchool,HarbinInstituteofTechnology,Shenzhen518055,China)4(SchoolofComputerScienceandTechnology,ShandongJianzhuUniv
4、ersity,Ji’nan250101,China)+Correspondingauthor:Phn:+86-10-82316732,E-mail:ezhang@263.net,http://nlsde.buaa.edu.cnZhangGW,LiDY,LiP,KangJC,ChenGS.Acollaborativefilteringrecommendationalgorithmbasedoncloudmodel.JournalofSoftware,2007,18(10):2403−2411.http://www.jos.org.cn
5、/1000-9825/18/2403.htmAbstract:Recommendationsystemisoneofthemostimportanttechnologiesappliedine-commerce.Similaritymeasuringmethodisfundamentaltocollaborativefilteringalgorithm,andtraditionalmethodsareinefficientespeciallywhentheuserratingdataareextremelysparse.Basedo
6、ntheoutstandingcharacteristicsofCloudModelontheprocessoftransformingaqualitativeconcepttoasetofquantitativenumericalvalues,anovelsimilaritymeasuringmethod,namelythelikenesscomparingmethodbasedoncloudmodel(LICM)isproposedinthispaper.LICMcomparesthesimilarityoftwouserson
7、knowledgelevel,whichcanovercomethedrawbackofattributes’strictlymatching.Thisworkanalysistraditionalmethodsthroughlyandputsforwardanovelcollaborativefilteringalgorithm,whichisbasedontheLICMmethod.Experimentsontypicaldatasetshowtheexcellentperformanceofthepresentcollabor
8、ativefilteringalgorithmbasedonLICM,evenwithextremelysparsityofdata.Keywords:cloudmodel;collaborativefiltering;similar
