personpagerank
pagerank 时间:2021-04-19 阅读:()
Topic-SensitivePageRankPresentedby:BratislavV.
Stojanoviunimatrix0@live.
comUniversityofBelgradeSchoolofElectricalEngineeringPage1/29IntroductionTheWorldWideWebisgrowingrapidlyTherearemorethan100millionwebsitesandmorethan10billionpagesoverthere!
Wedidn'tmentionthecontentthatcannotbeindexedbystandardsearchengines(Deepweb)!
Forexample,ifwetypetheword"golf"insideGoogle,wewillendupwitharound456millionresults!
Othersearchengineswillyieldmoreorlessdifferentresults.
Why"Whatmakesthefoundationofthesearchengine""Whydowepreferonesearchengineoveranother"BratislavStojanovi(unimatrix0@live.
com)|Page2/29ProblemDefinition"HowcanwefindexactlywhatwewantontheWWWinafastandefficientmatter"Everysearchengineneedstorankpages,buthowBiggerthevaluemeansthepagehasmorecontentBiggerthevaluemeansquerywordsaremorefrequentBiggerthevaluemeansthepageismoreimportantEverypagehasitsownrankofimportance,butwhatisimportanceTrafficanalysisFinancialstatementanalysisLinkstructureanalysis$$$BratislavStojanovi(unimatrix0@live.
com)|Page3/29ProblemImportanceNearly90%oftraffictomostwebsitesisfoundbyusingasearchengineordirectoryBratislavStojanovi(unimatrix0@live.
com)|Page4/29WheredousersclickmoreoftenWhatwillbetheresultofthequery"golf"ProblemTrendOureverydaylifeisclutteredwithatonsofdifferentinformationsFindingarealinformationhasbecomeevenmoredifficultTherehasbeenacoupleofmillionnewwebsitesadded,onlyinthelastyear!
Googleisthemostpopularwebsite,andthesecondmostvisitedwebsiteontheplanet!
BratislavStojanovi(unimatrix0@live.
com)|Page5/29ExistingSolutionsHITS(Hyperlink-InducedTopicSearch)HyperSearchPageRankHilltopSALSA(StochasticApproachforLinkStructureAnalysis)TrustRankAndmanyothervariants…BratislavStojanovi(unimatrix0@live.
com)|Page6/29Solution#1:HITSHubsandAuthoritiesJohnM.
Kleinberg,CornellUniversity,NY,'98ReflectsthetimewhentheinternetwasoriginallyformingTwotypesofpages:HubsAuthoritiesHubpageprovideslinkstogoodauthoritiesonthesubjectAuthoritypageprovidesagoodinformationaboutthesubjectBratislavStojanovi(unimatrix0@live.
com)|Page7/29Solution#1:HITSCriticism:ExpensiveatruntimeScoresarecalculatedusingsubgraphoftheentireWebgraphSimpleanditerativeQuery-specificrankscoreBratislavStojanovi(unimatrix0@live.
com)|Page8/29Solution#2:PageRankLawrence"Larry"Page,SergeyBrin,Stanford,1998UsedbytheGooglesearchengineUsesarandomsurfermodelRepresentsthelikelihoodthatapersonrandomlyclickingonlinkswillarriveatanyparticularpageProbabilitydistributionisevenlydividedamongallpagesintheWebgraphPageRankvalueiscomputedforeachpageofflineInterpretsahyperlinkfrompageitopagejasavote,bypagei,forpagejAnalyzesthepagethatcaststhevoteaswellBratislavStojanovi(unimatrix0@live.
com)|Page9/29Solution#2:PageRank"Pageisimportantifmanyimportantpagespointtoit"SimplifiedPageRankformula:r=PR(G)Input:WebgraphG=(V,E)Output:RankvectorrLetGhavennodes(pages)In-linksofpagei:HyperlinksthatpointtopageifromotherpagesOut-linksofpagei:HyperlinksthatpointouttootherpagesfrompageiBratislavStojanovi(unimatrix0@live.
com)|Page10/29Solution#2:PageRankOriginalPageRankformula:Dampingfactord=0.
85Moregeneralformula:Recursivedefinition!
Equationoftheeigensystem,wherethesolutiontoPisaneigenvectorwiththecorrespondingeigenvalueof1ComputationcanbedoneusingpoweriterationmethodBratislavStojanovi(unimatrix0@live.
com)|Page11/29Solution#2:PageRankBratislavStojanovi(unimatrix0@live.
com)|Page12/29P1P2P3P4I11111I2I3I4I5111110.
330.
330.
330.
50.
51P1P2P3P4I11111I211.
830.
330.
83I3I4I511.
830.
330.
830.
330.
330.
330.
1650.
1650.
831.
83P1P2P3P4I11111I211.
830.
330.
83I31.
831.
3250.
330.
495I4I51.
3251.
830.
330.
4950.
610.
610.
610.
1650.
1651.
3250.
495P1P2P3P4I11111I211.
830.
330.
83I31.
831.
3250.
330.
495I41.
3251.
270.
610.
775I51.
271.
3250.
610.
7750.
4420.
4420.
4421.
270.
3050.
3050.
775P1P2P3P4I11111I211.
830.
330.
83I31.
831.
3250.
330.
495I41.
3251.
270.
610.
775I51.
271.
5220.
4420.
7471.
5221.
270.
4420.
747ConvergesDEPENDS!
Solution#2:PageRankCriticism:QueryindependentrankscoreRandomsurfermodelnotappropriateinsomesituationsPronetomanipulations(Googlebombs,linkfarms…)InexpensiveatruntimeScoresarecalculatedusingtheentireWebgraphAlgorithmhashooksfor"personalization"BratislavStojanovi(unimatrix0@live.
com)|Page13/29Solution#3:TrustRankGyngyi,Garcia-Molina,Pedersen,Stanford&Yahoo!
,2004LinkanalysisalgorithmFindsmotivationinPageRankmanipulationUsedtosemi-automaticallyseparateusefulwebpagesfromspamWebspampagesarecreatedonlywiththeintentionofmisleadingsearchenginesHumanexpertscaneasilyidentifyspampages,butit'stooexpensivetomanuallyevaluateeverythingBratislavStojanovi(unimatrix0@live.
com)|Page14/29Solution#3:TrustRankSelectasmallsetofseedpagestobeevaluatedbyanexpertNow,extendoutwardfromtheseedsetandseeksimilarpagesbyusinglinksAlternatively,wecanpickasmallsetofspampagesTRcanbeusedtocalculatespammassSpammassisthemeasureoftheimpactoflinkspammingonapagerankingInsteadofPR,wecalculateInversePR"Pagesarebadiftheylinktobadpages"BratislavStojanovi(unimatrix0@live.
com)|Page15/29Solution#3:TrustRankCriticism:Semi-automatedseparationofreputable,goodpagesfromspampagesIncontrasttoPR,TRdifferentiatesgoodandbadpagesBasedonagoodseedsetoflessthan200pages,resultshaveshownthatTRcaneffectivelyfilteroutspamBratislavStojanovi(unimatrix0@live.
com)|Page16/29ProposedSolutionTSPR(Topic-SensitivePageRank)TaherH.
Haveliwala,StanfordUniversity,2003"Personalized"versionofPageRankInsteadofcomputingasinglerankvector,whydon'twecomputeasetofrankvectors,oneforeach(basis)topicUsestheOpenDirectoryProjectasasourceofrepresentativebasistopics(http://www.
dmoz.
org)orYahoo!
Calculateintwosteps,fullyautomatically:Pre-processingQuery-processingPreprocessingstepiscalculatedoffline,justaswithordinaryPageRankBratislavStojanovi(unimatrix0@live.
com)|Page17/29IsitbetterQuery-specificrankscoreFullyautomatedMakeuseofcontextStillinexpensiveatruntimeBratislavStojanovi(unimatrix0@live.
com)|Page18/29IsitoriginalThefirsttopic-sensitivepersonalizationofPageRankSourceofideasformanyotherpossiblepersonalizationsTahergotajobatGoogleInc.
in2003asamemberofSearchQualityGroupCited994timesonGoogleScholarBratislavStojanovi(unimatrix0@live.
com)|Page19/29TrendSearchincontextandsemanticwebareverypopulartopicsnowadaysTheywillcertainlyplayasignificantroleinthenextstepoftheWorldWideWebevolutionTheSemanticWebasaglobalvisionhasremainedlargelyunrealizedThereisabeliefthatWeb3.
0willdramaticallyimprovethefunctionalityandusabilityofsearchenginesBratislavStojanovi(unimatrix0@live.
com)|Page20/29Topic-SensitivePageRank1/7PageRankformula:r=PR(G)Topic-SensitivePageRankformula:r=IPR(G,v)IPRstandsfor"Influenced"PageRankInput:WebgraphG=(V,E)InfluencevectorisavectorofbasistopicstOutput:ListofrankvectorsrItmapspageito:pageiimportance,WRTtopictiBratislavStojanovi(unimatrix0@live.
com)|Page21/29Topic-SensitivePageRank2/7Forthesakeofsimplicity,let'sconsidersomepageiandonly16topics(categories):WecanpickthemfromthefirstlevelofODPStep1isperformedonce,offline,duringWebcrawlItusesthefollowingiterativeapproach:BratislavStojanovi(unimatrix0@live.
com)|Page22/29Foreachtopiccjεv{//Part1:Calcvjvj[i]=0;if(iεpages(cj)){vj[i]=1/num(pages(cj))}//Part2:Calcrjrj[i]=IPR(W,vj[i]);}Topic-SensitivePageRank3/7BratislavStojanovi(unimatrix0@live.
com)|Page23/29Step2assumesthatwecalculatesomedistributionofweightsoverthe16topicsinourbasisOnlythelinkstructureofpagesrelevanttothequerytopicwillbeusedtorankpageiExample:Queryis"golf"Withnoadditionalcontext,thedistributionoftopicweightswewoulduseis:Topic-SensitivePageRank4/7BratislavStojanovi(unimatrix0@live.
com)|Page24/29Ifuserissuesqueriesaboutinvestmentopportunities,afollow-upqueryon"golf"shouldberankeddifferently,withthebusiness-specificrankvectorExample:Queryis"golf",butthepreviousquerywas"financialservicesinvestments"Distributionoftopicweightswewoulduseis:Topic-SensitivePageRank5/7BratislavStojanovi(unimatrix0@live.
com)|Page25/29Attheend,calculatethecompositePageRankscoreusingthefollowingformula:Interpretationofthecompositescore:WeightedsumofrankvectorsitselfformsavalidrankvectorThefinalscorecanbeusedinconjuctionwithotherscoringschemesTopic-SensitivePageRank6/7BratislavStojanovi(unimatrix0@live.
com)|Page26/29Topic:SportsTopic:SportsAfterawhile:P1(sports)=0.
895P1(business)=1.
2731111111P1P2P3P4P5P6P7I11111111I2Topic:BusinessTopic:Business11andsoon…Finally:P1(sports,business)==0.
55*0.
895+0.
85*1.
273=0.
533110.
330.
330.
330.
330.
330.
3310.
330.
330.
33P1P2P3P4P5P6P7I11111111I2110.
330.
660.
331.
331.
33P1P2P3P4P5P6I1I2P1P2P3P4P5P6I1111111I2110.
330.
660.
331.
331.
331111P1P2P3P4P5P6I1111111I2………………Topic-SensitivePageRank7/7BratislavStojanovi(unimatrix0@live.
com)|Page27/29ConclusionImplicitlymakesuseofIR(InformationRetrieval)indeterminingthetopicofthequeryHowever,thisuseofIRisNOTvulnerabletomanipulation,becauseODPiscompiledbythousandsofvolunteereditorsUsingasmallbasissetisimportantforkeepingthequery-timecostslowFuturework:UsefinergrainedbasissetWeightingschemebasedonpagesimilaritytoODPcategory,ratherthanpagemembershiptoODPcategoryBratislavStojanovi(unimatrix0@live.
com)|Page28/29QuestionsandDiscussionBratislavStojanovi(unimatrix0@live.
com)|Page29/29Yes
Stojanoviunimatrix0@live.
comUniversityofBelgradeSchoolofElectricalEngineeringPage1/29IntroductionTheWorldWideWebisgrowingrapidlyTherearemorethan100millionwebsitesandmorethan10billionpagesoverthere!
Wedidn'tmentionthecontentthatcannotbeindexedbystandardsearchengines(Deepweb)!
Forexample,ifwetypetheword"golf"insideGoogle,wewillendupwitharound456millionresults!
Othersearchengineswillyieldmoreorlessdifferentresults.
Why"Whatmakesthefoundationofthesearchengine""Whydowepreferonesearchengineoveranother"BratislavStojanovi(unimatrix0@live.
com)|Page2/29ProblemDefinition"HowcanwefindexactlywhatwewantontheWWWinafastandefficientmatter"Everysearchengineneedstorankpages,buthowBiggerthevaluemeansthepagehasmorecontentBiggerthevaluemeansquerywordsaremorefrequentBiggerthevaluemeansthepageismoreimportantEverypagehasitsownrankofimportance,butwhatisimportanceTrafficanalysisFinancialstatementanalysisLinkstructureanalysis$$$BratislavStojanovi(unimatrix0@live.
com)|Page3/29ProblemImportanceNearly90%oftraffictomostwebsitesisfoundbyusingasearchengineordirectoryBratislavStojanovi(unimatrix0@live.
com)|Page4/29WheredousersclickmoreoftenWhatwillbetheresultofthequery"golf"ProblemTrendOureverydaylifeisclutteredwithatonsofdifferentinformationsFindingarealinformationhasbecomeevenmoredifficultTherehasbeenacoupleofmillionnewwebsitesadded,onlyinthelastyear!
Googleisthemostpopularwebsite,andthesecondmostvisitedwebsiteontheplanet!
BratislavStojanovi(unimatrix0@live.
com)|Page5/29ExistingSolutionsHITS(Hyperlink-InducedTopicSearch)HyperSearchPageRankHilltopSALSA(StochasticApproachforLinkStructureAnalysis)TrustRankAndmanyothervariants…BratislavStojanovi(unimatrix0@live.
com)|Page6/29Solution#1:HITSHubsandAuthoritiesJohnM.
Kleinberg,CornellUniversity,NY,'98ReflectsthetimewhentheinternetwasoriginallyformingTwotypesofpages:HubsAuthoritiesHubpageprovideslinkstogoodauthoritiesonthesubjectAuthoritypageprovidesagoodinformationaboutthesubjectBratislavStojanovi(unimatrix0@live.
com)|Page7/29Solution#1:HITSCriticism:ExpensiveatruntimeScoresarecalculatedusingsubgraphoftheentireWebgraphSimpleanditerativeQuery-specificrankscoreBratislavStojanovi(unimatrix0@live.
com)|Page8/29Solution#2:PageRankLawrence"Larry"Page,SergeyBrin,Stanford,1998UsedbytheGooglesearchengineUsesarandomsurfermodelRepresentsthelikelihoodthatapersonrandomlyclickingonlinkswillarriveatanyparticularpageProbabilitydistributionisevenlydividedamongallpagesintheWebgraphPageRankvalueiscomputedforeachpageofflineInterpretsahyperlinkfrompageitopagejasavote,bypagei,forpagejAnalyzesthepagethatcaststhevoteaswellBratislavStojanovi(unimatrix0@live.
com)|Page9/29Solution#2:PageRank"Pageisimportantifmanyimportantpagespointtoit"SimplifiedPageRankformula:r=PR(G)Input:WebgraphG=(V,E)Output:RankvectorrLetGhavennodes(pages)In-linksofpagei:HyperlinksthatpointtopageifromotherpagesOut-linksofpagei:HyperlinksthatpointouttootherpagesfrompageiBratislavStojanovi(unimatrix0@live.
com)|Page10/29Solution#2:PageRankOriginalPageRankformula:Dampingfactord=0.
85Moregeneralformula:Recursivedefinition!
Equationoftheeigensystem,wherethesolutiontoPisaneigenvectorwiththecorrespondingeigenvalueof1ComputationcanbedoneusingpoweriterationmethodBratislavStojanovi(unimatrix0@live.
com)|Page11/29Solution#2:PageRankBratislavStojanovi(unimatrix0@live.
com)|Page12/29P1P2P3P4I11111I2I3I4I5111110.
330.
330.
330.
50.
51P1P2P3P4I11111I211.
830.
330.
83I3I4I511.
830.
330.
830.
330.
330.
330.
1650.
1650.
831.
83P1P2P3P4I11111I211.
830.
330.
83I31.
831.
3250.
330.
495I4I51.
3251.
830.
330.
4950.
610.
610.
610.
1650.
1651.
3250.
495P1P2P3P4I11111I211.
830.
330.
83I31.
831.
3250.
330.
495I41.
3251.
270.
610.
775I51.
271.
3250.
610.
7750.
4420.
4420.
4421.
270.
3050.
3050.
775P1P2P3P4I11111I211.
830.
330.
83I31.
831.
3250.
330.
495I41.
3251.
270.
610.
775I51.
271.
5220.
4420.
7471.
5221.
270.
4420.
747ConvergesDEPENDS!
Solution#2:PageRankCriticism:QueryindependentrankscoreRandomsurfermodelnotappropriateinsomesituationsPronetomanipulations(Googlebombs,linkfarms…)InexpensiveatruntimeScoresarecalculatedusingtheentireWebgraphAlgorithmhashooksfor"personalization"BratislavStojanovi(unimatrix0@live.
com)|Page13/29Solution#3:TrustRankGyngyi,Garcia-Molina,Pedersen,Stanford&Yahoo!
,2004LinkanalysisalgorithmFindsmotivationinPageRankmanipulationUsedtosemi-automaticallyseparateusefulwebpagesfromspamWebspampagesarecreatedonlywiththeintentionofmisleadingsearchenginesHumanexpertscaneasilyidentifyspampages,butit'stooexpensivetomanuallyevaluateeverythingBratislavStojanovi(unimatrix0@live.
com)|Page14/29Solution#3:TrustRankSelectasmallsetofseedpagestobeevaluatedbyanexpertNow,extendoutwardfromtheseedsetandseeksimilarpagesbyusinglinksAlternatively,wecanpickasmallsetofspampagesTRcanbeusedtocalculatespammassSpammassisthemeasureoftheimpactoflinkspammingonapagerankingInsteadofPR,wecalculateInversePR"Pagesarebadiftheylinktobadpages"BratislavStojanovi(unimatrix0@live.
com)|Page15/29Solution#3:TrustRankCriticism:Semi-automatedseparationofreputable,goodpagesfromspampagesIncontrasttoPR,TRdifferentiatesgoodandbadpagesBasedonagoodseedsetoflessthan200pages,resultshaveshownthatTRcaneffectivelyfilteroutspamBratislavStojanovi(unimatrix0@live.
com)|Page16/29ProposedSolutionTSPR(Topic-SensitivePageRank)TaherH.
Haveliwala,StanfordUniversity,2003"Personalized"versionofPageRankInsteadofcomputingasinglerankvector,whydon'twecomputeasetofrankvectors,oneforeach(basis)topicUsestheOpenDirectoryProjectasasourceofrepresentativebasistopics(http://www.
dmoz.
org)orYahoo!
Calculateintwosteps,fullyautomatically:Pre-processingQuery-processingPreprocessingstepiscalculatedoffline,justaswithordinaryPageRankBratislavStojanovi(unimatrix0@live.
com)|Page17/29IsitbetterQuery-specificrankscoreFullyautomatedMakeuseofcontextStillinexpensiveatruntimeBratislavStojanovi(unimatrix0@live.
com)|Page18/29IsitoriginalThefirsttopic-sensitivepersonalizationofPageRankSourceofideasformanyotherpossiblepersonalizationsTahergotajobatGoogleInc.
in2003asamemberofSearchQualityGroupCited994timesonGoogleScholarBratislavStojanovi(unimatrix0@live.
com)|Page19/29TrendSearchincontextandsemanticwebareverypopulartopicsnowadaysTheywillcertainlyplayasignificantroleinthenextstepoftheWorldWideWebevolutionTheSemanticWebasaglobalvisionhasremainedlargelyunrealizedThereisabeliefthatWeb3.
0willdramaticallyimprovethefunctionalityandusabilityofsearchenginesBratislavStojanovi(unimatrix0@live.
com)|Page20/29Topic-SensitivePageRank1/7PageRankformula:r=PR(G)Topic-SensitivePageRankformula:r=IPR(G,v)IPRstandsfor"Influenced"PageRankInput:WebgraphG=(V,E)InfluencevectorisavectorofbasistopicstOutput:ListofrankvectorsrItmapspageito:pageiimportance,WRTtopictiBratislavStojanovi(unimatrix0@live.
com)|Page21/29Topic-SensitivePageRank2/7Forthesakeofsimplicity,let'sconsidersomepageiandonly16topics(categories):WecanpickthemfromthefirstlevelofODPStep1isperformedonce,offline,duringWebcrawlItusesthefollowingiterativeapproach:BratislavStojanovi(unimatrix0@live.
com)|Page22/29Foreachtopiccjεv{//Part1:Calcvjvj[i]=0;if(iεpages(cj)){vj[i]=1/num(pages(cj))}//Part2:Calcrjrj[i]=IPR(W,vj[i]);}Topic-SensitivePageRank3/7BratislavStojanovi(unimatrix0@live.
com)|Page23/29Step2assumesthatwecalculatesomedistributionofweightsoverthe16topicsinourbasisOnlythelinkstructureofpagesrelevanttothequerytopicwillbeusedtorankpageiExample:Queryis"golf"Withnoadditionalcontext,thedistributionoftopicweightswewoulduseis:Topic-SensitivePageRank4/7BratislavStojanovi(unimatrix0@live.
com)|Page24/29Ifuserissuesqueriesaboutinvestmentopportunities,afollow-upqueryon"golf"shouldberankeddifferently,withthebusiness-specificrankvectorExample:Queryis"golf",butthepreviousquerywas"financialservicesinvestments"Distributionoftopicweightswewoulduseis:Topic-SensitivePageRank5/7BratislavStojanovi(unimatrix0@live.
com)|Page25/29Attheend,calculatethecompositePageRankscoreusingthefollowingformula:Interpretationofthecompositescore:WeightedsumofrankvectorsitselfformsavalidrankvectorThefinalscorecanbeusedinconjuctionwithotherscoringschemesTopic-SensitivePageRank6/7BratislavStojanovi(unimatrix0@live.
com)|Page26/29Topic:SportsTopic:SportsAfterawhile:P1(sports)=0.
895P1(business)=1.
2731111111P1P2P3P4P5P6P7I11111111I2Topic:BusinessTopic:Business11andsoon…Finally:P1(sports,business)==0.
55*0.
895+0.
85*1.
273=0.
533110.
330.
330.
330.
330.
330.
3310.
330.
330.
33P1P2P3P4P5P6P7I11111111I2110.
330.
660.
331.
331.
33P1P2P3P4P5P6I1I2P1P2P3P4P5P6I1111111I2110.
330.
660.
331.
331.
331111P1P2P3P4P5P6I1111111I2………………Topic-SensitivePageRank7/7BratislavStojanovi(unimatrix0@live.
com)|Page27/29ConclusionImplicitlymakesuseofIR(InformationRetrieval)indeterminingthetopicofthequeryHowever,thisuseofIRisNOTvulnerabletomanipulation,becauseODPiscompiledbythousandsofvolunteereditorsUsingasmallbasissetisimportantforkeepingthequery-timecostslowFuturework:UsefinergrainedbasissetWeightingschemebasedonpagesimilaritytoODPcategory,ratherthanpagemembershiptoODPcategoryBratislavStojanovi(unimatrix0@live.
com)|Page28/29QuestionsandDiscussionBratislavStojanovi(unimatrix0@live.
com)|Page29/29Yes
- personpagerank相关文档
- belongingpagerank
- originatingpagerank
- matrixpagerank
- errorpagerank
- estimatepagerank
- pagepagerank
RAKsmartCloud服务器,可自定义配置月$7.59
RAKsmart商家一直以来在独立服务器、站群服务器和G口和10G口大端口流量服务器上下功夫比较大，但是在VPS主机业务上仅仅是顺带，尤其是我们看到大部分主流商家都做云服务器，而RAKsmart商家终于开始做云服务器，这次试探性的新增美国硅谷机房一个方案。月付7.59美元起，支持自定义配置，KVM虚拟化，美国硅谷机房，VPC网络/经典网络，大陆优化/精品网线路，支持Linux或者Windows操作...
美得云（20元）香港特价将军澳CTG+CN2云服务器
美得云成立于2021年，是一家云产品管理服务商（cloud）专业提供云计算服务、DDOS防护、网络安全服务、国内海外数据中心托管租用等业务、20000+用户的选择，43800+小时稳定运行香港特价将军澳CTG+CN2云服务器、采用高端CPU 优质CN2路线 SDD硬盘。香港CTG+CN22核2G3M20G数据盘25元点击购买香港CTG+CN22核2G5M30G数据盘39元点击购买香港CTG+CN...
陆零（￥25）云端专用的高性能、安全隔离的物理集群六折起
陆零网络是正规的IDC公司，我们采用优质硬件和网络，为客户提供高速、稳定的云计算服务。公司拥有一流的技术团队，提供7*24小时1对1售后服务，让您无后顾之忧。我们目前提供高防空间、云服务器、物理服务器，高防IP等众多产品，为您提供轻松上云、安全防护 为核心数据库、关键应用系统、高性能计算业务提供云端专用的高性能、安全隔离的物理集群。分钟级交付周期助你的企业获得实时的业务响应能力，助力核心业务飞速成...
pagerank为你推荐
-
支付宝调整还款日支付宝调整花呗还款日，这个调整有没有对你造成什么影响？波音737起飞爆胎美国737MAX又紧急迫降，为什么它还在飞？重庆400年老树穿楼生长生长百年的老树,仍能不断生长,是因为主要有什么组织www.topit.me提供好的图片网站文档下载怎样把手机里的文件直接下载或复制到U盘里开放平台企鹅号和腾讯内容开放平台是一样的吗，有什么区别？购物车（淘宝）为什么推荐购物车购买,是什么意思啊?95188是什么电话95188是什么号码我刚收到短信是什么支付宝的验证码闪拍网闪拍网是真的吗瑞东集团中粮集团主要生产什么的？是国企么