捆绑销售系统外文文献翻译

捆绑销售系统外文文献翻译

ID:47903846

大小:79.50 KB

页数:18页

时间:2019-10-22

捆绑销售系统外文文献翻译_第1页
捆绑销售系统外文文献翻译_第2页
捆绑销售系统外文文献翻译_第3页
捆绑销售系统外文文献翻译_第4页
捆绑销售系统外文文献翻译_第5页
资源描述:

《捆绑销售系统外文文献翻译》由会员上传分享,免费在线阅读,更多相关内容在工程资料-天天文库

1、外文文献翻译原文及译文标题:Recommendersystemsforproductbundling作者:MoranBeladev,LiorRokach,ErachaShapira193-206期刊:Knowledge-BasedSystems,卷111,页码:年份:2016原文RecommendersystemsforproductbundlingMoranBeladev,LiorRokach,BrachaShapiraAbstractRecommendersystems(RS)areaclassofinformationfi

2、lterapplicationswhosemaingoalistoprovidepersonalizedrecommendations,content,andservicestousers・Recommendationservicesmaysupportafirm'smarketingstrategyandcontributetoincreaserevenues・MostRSmethodsweredesignedtoproviderecommendationsofsingleitems・Generatingbundlerecom

3、mendations,i.e.,recommendationsoftwoormoreitemstogether,cansatisfyconsumerneeds,whileatthesametimeincreasecustomers9buyingscopeandthefirm*sincome・Thus,findingandrecommendinganoptimalandpersonalbundlebecomesveryimportant.Recommendationofbundlesofproductsshouldalsoinvo

4、lvepersonalizedpricingtopredictwhichpriceshouldbeofferedtoauserinorderforthebundletomaximizepurchaseprobability・However,mostrecommendationmethodsdonotinvolvesuchpersonalpriceadjustment.Thispaperintroducesanovelmodelofbundlerecommendationsthatintegratescollaborativefi

5、ltering(CF)techniques,demandfunctions,andpricemodeling.Thismodelmaximizestheexpectedrevenueofarecommendationlistbyfindingpairsofproductsandpricingtheminawaythatmaximizesboththeprobabilityofitspurchasebytheuserandtherevenuereceivedbysellingthebundle・Experimentswithsev

6、eralreal-worlddatasetshavebeenconductedinordertoevaluatetheaccuracyofthebundlingmodelpredictions.Thispapercomparestheproposedmethodwithseveralstate-of-the-artmethods(collaborativefilteringandSVD).Ithasbeenfoundthatusingbundlerecommendationcanimprovetheaccuracyofresul

7、ts.Furthermore,thesuggestedpricerecommendationmodelprovidesagoodestimateoftheactualpricepaidbytheuserandatthesametimecanincreasethefirm'sincome.Keywords:Recommendersystems,Productbundling,Pricebundling,E-commerce,Collaborativefiltering,SVDIntroductionRecommendersyste

8、msareaclassofinformationfilterapplicationswhosemaingoalistoprovidepersonalizedrecommendationsofcontentandservicestousers・Arecommend

当前文档最多预览五页,下载文档查看全文

此文档下载收益归作者所有

当前文档最多预览五页,下载文档查看全文
温馨提示:
1. 部分包含数学公式或PPT动画的文件,查看预览时可能会显示错乱或异常,文件下载后无此问题,请放心下载。
2. 本文档由用户上传,版权归属用户,天天文库负责整理代发布。如果您对本文档版权有争议请及时联系客服。
3. 下载前请仔细阅读文档内容,确认文档内容符合您的需求后进行下载,若出现内容与标题不符可向本站投诉处理。
4. 下载文档时可能由于网络波动等原因无法下载或下载错误,付费完成后未能成功下载的用户请联系客服处理。