{"title":"你为什么要推荐我那个?","authors":"Aish Fenton","doi":"10.1145/2948674.2948681","DOIUrl":null,"url":null,"abstract":"With so many advances in machine learning recently, it's not unreasonable to ask: why aren't my recommendations perfect by now? Aish provides a walkthrough of the open problems in the area of recommender systems, especially as they apply to Netflix's personalization and recommender algorithms. He also provides a brief overview of recommender systems, and sketches out some tentative solutions for the problems he presents.","PeriodicalId":165112,"journal":{"name":"Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why would you recommend me that!?\",\"authors\":\"Aish Fenton\",\"doi\":\"10.1145/2948674.2948681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With so many advances in machine learning recently, it's not unreasonable to ask: why aren't my recommendations perfect by now? Aish provides a walkthrough of the open problems in the area of recommender systems, especially as they apply to Netflix's personalization and recommender algorithms. He also provides a brief overview of recommender systems, and sketches out some tentative solutions for the problems he presents.\",\"PeriodicalId\":165112,\"journal\":{\"name\":\"Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2948674.2948681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2948674.2948681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
With so many advances in machine learning recently, it's not unreasonable to ask: why aren't my recommendations perfect by now? Aish provides a walkthrough of the open problems in the area of recommender systems, especially as they apply to Netflix's personalization and recommender algorithms. He also provides a brief overview of recommender systems, and sketches out some tentative solutions for the problems he presents.