个性化网络教学资源系统的构建的研究

个性化网络教学资源系统的构建的研究

ID:34004670

大小:1.96 MB

页数:46页

时间:2019-03-03

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1、AbstractWiththedevelopmentofInternet,ithasbecomeanimportantwaytoobtaininformation.Usershavetheexponentialgrowthofresources.Butithasbecomeincreasinglyhardtofindtheinformationtheywant.Basedonthis,thedevelopmentandutilizationofpersonalizedrecommendationtechnology

2、isagoodsolutiontosolveinformationoverload.Personalizedrecommendationisakindofnewintelligentinformationservice.Accordingtoanalyzingtheirrequirementsbyuser’sregisterandhistoryofbehavior,personalizedrecommendationcanaccuratelyprovidetheinformationusersareinterest

3、edin.Toacertainextent,personalizedrecommendationsolvestheinformationlostandinformationoverloadwhichbroughtaboutvariousproblems.Withthedevelopmentofpersonalizedrecommendationtechnologyresearch,popularizationandapplicationofthepersonalizedrecommendationsystemisb

4、ecomingtheresearchhotspots.Asanintegralpartofinformationtechnology,teachingresourcesplayanimportantroleineducation.Atpresent,networkteachingresourcesystemstypicallyprovidethesameresourcestouser.Butusers’havedifferentinterestsandhobbies.Thatisindividualdifferen

5、ces.Theexistingnetworkteachingresourcessystemcannotmeetuser'spersonalizedneeds.Therefore,inordertoachievethegoalofpersonalizedservicetomeetuser,personalizedrecommendationtechnologyisappliedtothesystemofonlineteachingresources.Throughanalyzingandcomparingalotof

6、literatureresearch,combiningthecontent-basedandcollaborativefilteringofpersonalizedrecommendationalgorithmcanhelpusersidentifypotentialhobbiesandmakerecommendations.Itcanhelpusersquicklyfindthattheyneedinalargenumberofinformationresourcesandmeetusers’demandfor

7、personalizedservice.Asaresult,thisarticleusescombinationofthecontent-basedandcollaborativefilteringrecommendationtorecommendpersonalizedteachingresources.First,thepaperdescribestheproblemsofthecurrentnetworkofteachingresourcesandtheresearchstatusoftheindividua

8、lizedteachingservices.Thenthekeytechniquesofpersonalrecommendationtechnologyandusermodelingareintroduced.Second,personalrecommendationalgorithmisthecoreofpersonalizedrecommendation

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