Emine Yilmaz, Milad Shokouhi, Nick Craswell, S. Robertson
{"title":"预期浏览实用程序的网络搜索评估","authors":"Emine Yilmaz, Milad Shokouhi, Nick Craswell, S. Robertson","doi":"10.1145/1871437.1871672","DOIUrl":null,"url":null,"abstract":"Most information retrieval evaluation metrics are designed to measure the satisfaction of the user given the results returned by a search engine. In order to evaluate user satisfaction, most of these metrics have underlying user models, which aim at modeling how users interact with search engine results. Hence, the quality of an evaluation metric is a direct function of the quality of its underlying user model. This paper proposes EBU, a new evaluation metric that uses a sophisticated user model tuned by observations over many thousands of real search sessions. We compare EBU with a number of state of the art evaluation metrics and show that it is more correlated with real user behavior captured by clicks.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"95","resultStr":"{\"title\":\"Expected browsing utility for web search evaluation\",\"authors\":\"Emine Yilmaz, Milad Shokouhi, Nick Craswell, S. Robertson\",\"doi\":\"10.1145/1871437.1871672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most information retrieval evaluation metrics are designed to measure the satisfaction of the user given the results returned by a search engine. In order to evaluate user satisfaction, most of these metrics have underlying user models, which aim at modeling how users interact with search engine results. Hence, the quality of an evaluation metric is a direct function of the quality of its underlying user model. This paper proposes EBU, a new evaluation metric that uses a sophisticated user model tuned by observations over many thousands of real search sessions. We compare EBU with a number of state of the art evaluation metrics and show that it is more correlated with real user behavior captured by clicks.\",\"PeriodicalId\":310611,\"journal\":{\"name\":\"Proceedings of the 19th ACM international conference on Information and knowledge management\",\"volume\":\"2013 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"95\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 19th ACM international conference on Information and knowledge management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1871437.1871672\",\"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 19th ACM international conference on Information and knowledge management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1871437.1871672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Expected browsing utility for web search evaluation
Most information retrieval evaluation metrics are designed to measure the satisfaction of the user given the results returned by a search engine. In order to evaluate user satisfaction, most of these metrics have underlying user models, which aim at modeling how users interact with search engine results. Hence, the quality of an evaluation metric is a direct function of the quality of its underlying user model. This paper proposes EBU, a new evaluation metric that uses a sophisticated user model tuned by observations over many thousands of real search sessions. We compare EBU with a number of state of the art evaluation metrics and show that it is more correlated with real user behavior captured by clicks.