T. Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, P. Cremonesi, Roberto Pagano, Massimo Quadrana
{"title":"多堆栈集成的工作推荐","authors":"T. Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, P. Cremonesi, Roberto Pagano, Massimo Quadrana","doi":"10.1145/2987538.2987541","DOIUrl":null,"url":null,"abstract":"This paper describes the approach that team PumpkinPie adopted in the 2016 Recsys Challenge. The task of the competition organized by XING is to predict which job postings the user has interacted with. The team's approach mainly consists in generating a set of models using different techniques, and then combining them in a multi-stack ensemble. This strategy granted the fourth position in the final leader-board to the team, with an overall score of 1.86M.","PeriodicalId":127880,"journal":{"name":"RecSys Challenge '16","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Multi-stack ensemble for job recommendation\",\"authors\":\"T. Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, P. Cremonesi, Roberto Pagano, Massimo Quadrana\",\"doi\":\"10.1145/2987538.2987541\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the approach that team PumpkinPie adopted in the 2016 Recsys Challenge. The task of the competition organized by XING is to predict which job postings the user has interacted with. The team's approach mainly consists in generating a set of models using different techniques, and then combining them in a multi-stack ensemble. This strategy granted the fourth position in the final leader-board to the team, with an overall score of 1.86M.\",\"PeriodicalId\":127880,\"journal\":{\"name\":\"RecSys Challenge '16\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"RecSys Challenge '16\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2987538.2987541\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"RecSys Challenge '16","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2987538.2987541","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes the approach that team PumpkinPie adopted in the 2016 Recsys Challenge. The task of the competition organized by XING is to predict which job postings the user has interacted with. The team's approach mainly consists in generating a set of models using different techniques, and then combining them in a multi-stack ensemble. This strategy granted the fourth position in the final leader-board to the team, with an overall score of 1.86M.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
