个性化营养菜谱推荐方法的分析-(5418)

个性化营养菜谱推荐方法的分析-(5418)

ID:33762495

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页数:70页

时间:2019-03-01

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1、万方数据ABSTRACTInrecentyears,theInteractisgraduallyoverthrowingthetraditionalindustrieswithbusinessmodesrepresentedby“OnlineToOffiine(020)”.Manytraditionalindustriesstarttoprovideuserswithhigh-qualityandmorepersonalizedservicesbyusingtheInteract.Forexam

2、ple,arestaurantcouldlargelyimproveusers’experienceandincreaseitscompetitiveness,whichsupports020modeandprovidescustomerswithnutrientandpersonalizedmenus.ThesystembuiltbypersonalizednutrientreciperecommendationinthisthesisisexactlyasystemwhichCaneasil

3、yprovideusers、析Ⅱ1convenientpersonalizednutrientrecipe.Theriseofonlinemealorderingmakesthesystemofgreatapplicationvalue.Thepersonalizednutrientreciperecommendationsysteminthisthesisincludesthreeparts:thefrontdesktoshowtheDemo,thecorealgorithmsandbacke

4、nddatabase.Thecorealgorithm,namelypersonalizednutrientreciperecommendationmethod,includesdataacquisitionalgorithm,nutritionarrangealgorithmandpersonalizedrecommendationalgorithm.Thisthesiscardedoutresearchonthedesignofsystemandcorealgorithm,themainwo

5、rkisasfollows:1.Puttingforwardafocusedwebcrawlerbasedondouble-queuesortingandmodelself-learningtocrawlIntemetinformationrelatedtoaspecifictopic.Basedontheexistingfocusedwebcrawlerframework,thecrawlerusesdoubleorderedqueuesanddepthattributeoftheURLtoe

6、nhancetheperformanceofsearchstrategymodule,andusesthebloomfiltertooptimizethemoduleofremovingduplicateURL(uniformResourceLocator).Thedataanalysismoduleisoptimizedbyseparatecalculationofthetopiccorrelationofparent—pageandsubpage.Anewmoduleofmodelself-

7、learningisaddedaswell.ThenwegivesthecomparativeexperimentsofthiscrawlerwiⅡlthegeneralwebcrawlerandthedoublequeuetopicwebcrawler,andtheresultshowsthattheharvestRateofthiscrawlerismuchhigher.2。PuttingforwardageneticalgorithmbasedonLdominationandteamcom

8、petitiontosolvemulti-objectiveoptimizationproblemsinhigh·dimensionalspace.Thisalgorithmputsthenon-dominatedsortinggeneticalgorithrnIIasthebasicframework,andusesLdominatedmethodandgroupcompetitionbasedoncrowdingdistancetogetnon-dominatedsorting,select

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