{"title":"推荐世界知识:Quora推荐系统的应用","authors":"Lei Yang, X. Amatriain","doi":"10.1145/2959100.2959128","DOIUrl":null,"url":null,"abstract":"At Quora, our mission is to share and grow the world's knowledge. Recommender systems are at the core of this mission: we need to recommend the most important questions to people most likely to write great answers, and recommend the best answers to people interested in reading them. Driven by the above mission statement, we have a variety of interesting and challenging recommendation problems and a large, rich data set that we can work with to build novel solutions for them. In this talk, we will describe several of these recommendation problems and present our approaches solving them.","PeriodicalId":315651,"journal":{"name":"Proceedings of the 10th ACM Conference on Recommender Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Recommending the World's Knowledge: Application of Recommender Systems at Quora\",\"authors\":\"Lei Yang, X. Amatriain\",\"doi\":\"10.1145/2959100.2959128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At Quora, our mission is to share and grow the world's knowledge. Recommender systems are at the core of this mission: we need to recommend the most important questions to people most likely to write great answers, and recommend the best answers to people interested in reading them. Driven by the above mission statement, we have a variety of interesting and challenging recommendation problems and a large, rich data set that we can work with to build novel solutions for them. In this talk, we will describe several of these recommendation problems and present our approaches solving them.\",\"PeriodicalId\":315651,\"journal\":{\"name\":\"Proceedings of the 10th ACM Conference on Recommender Systems\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 10th ACM Conference on Recommender Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2959100.2959128\",\"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 10th ACM Conference on Recommender Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2959100.2959128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recommending the World's Knowledge: Application of Recommender Systems at Quora
At Quora, our mission is to share and grow the world's knowledge. Recommender systems are at the core of this mission: we need to recommend the most important questions to people most likely to write great answers, and recommend the best answers to people interested in reading them. Driven by the above mission statement, we have a variety of interesting and challenging recommendation problems and a large, rich data set that we can work with to build novel solutions for them. In this talk, we will describe several of these recommendation problems and present our approaches solving them.