预览加载中,请您耐心等待几秒...
1/10
2/10
3/10
4/10
5/10
6/10
7/10
8/10
9/10
10/10

亲,该文档总共57页,到这已经超出免费预览范围,如果喜欢就直接下载吧~

如果您无法下载资料,请参考说明:

1、部分资料下载需要金币,请确保您的账户上有足够的金币

2、已购买过的文档,再次下载不重复扣费

3、资料包下载后请先用软件解压,在使用对应软件打开

基于深度学习的商品推荐系统研究学学统学学161203105374·学学2020的基于深度学习的商品推荐系统研究的研究的的的学学2020基于深度学习的商品推荐系统研究推荐的商品统深度学习推荐系统研究2018.11.162018.12.16的8477商品基于商品度RPythonLRGBDTDeepFM推荐系统DeepFMLRGBDT的商品推荐商推荐系统的商品的推推荐系统DeepFMGBDTLR学学2020ResearchonCommodityRecommendationSystemBasedonDeepLearningAbstractInordertomorequicklyandaccuratelyrecommendproductsofinteresttousersthispaperstudiestherecommendationsystemfromthreedirectionssuchastraditionalalgorithmanddatamininganddeeplearning.Alibaba'sproductbehaviordataof8477usersfromNovem-ber16toDecember162018areselected.Featureextractionisbasedontwodimensionsofusersandgoods.AndweuseRandPythontoimplementtherecommendationsystemforLRandGBDTandDeepFMrespectively.FinallyweconcludethatDeepFMhasbetterpredictioneffectthanLRandGBDT.Itcanmoreaccuratelyjudgewhethertorecommendornotforuserstobuythisproduct.Italsogivessomesuggestionstothemerchants.Throughthepredictionoftherecommendationsystemitcanpromotetheuserswho