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ID:59508390
大小:524.30 KB
页数:11页
时间:2020-09-04
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1、Towardslatentcontext-awarerecommendationsystemsContext-awarerecommendersystem(CARS)Theareaofcontext-awarerecommendersystems(CARS)dealswithmodelingandpredictingusertastesandpreferencesbyincorporatingavailablecontextualinformationintotherecommendationpr
2、ocessasexplicitadditionalcategoriesofdata.衣服推荐系统美食推荐系统阅读推荐系统Maincontributionwesuggestseveralmethodsofextractinglatentcontextfromthedatacollectedfrommobiledevicesensors.weshowhowtoutilizetheselatentcontextsanddescribeanovelrecommendationtechniquethatus
3、eslatentcontextsandimprovestheaccuracyofstate-of-the-artCARS.Inordertoreducethedimensionality,wesuggestextractinglatentcontextswithtwounsupervisedtechniques:deeplearning(2)principalcomponentanalysis(PCA).extractinglatentcontextLatentcontextextraction
4、usingauto-encoderAnauto-encoderneuralnetworkisanunsupervisedlearningalgorithmthatappliesbackpropagation,settingthetargetvaluesasequaltotheinputsByusingadeepauto-encoder,thedeeplayersrevealthelong-termpatternsoftheuserthatcanbetranslatedtolatentcontext
5、.Latentcontextextractionusingprincipalcomponentanalysis(PCA)PCAisadimensionalreductionmethodthatusesanorthogonaltransformationtoconvertasetofobservationswithpossiblecorrelatedvariablesintoasetofnewuncorrelatedfeaturesRatingmodelThankyou!
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