{"title":"关于搜索的科学:统计方法，评估，优化","authors":"S. Robertson","doi":"10.1145/1364742.1364745","DOIUrl":null,"url":null,"abstract":"This paper, based on a talk, presents an overview of evaluation experiments in information retrieval, and also of statistical approaches to search. A strong connection exists between them: the notion that the objective of search can be expressed in terms of the measures used for evaluation informs the statistical theory in several ways. The latest manifestation of this connection is the work on optimization of ranking algorithms, using machine learning techniques.","PeriodicalId":287514,"journal":{"name":"International Workshop On Research Issues in Digital Libraries","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the science of search: statistical approaches, evaluation, optimisation\",\"authors\":\"S. Robertson\",\"doi\":\"10.1145/1364742.1364745\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper, based on a talk, presents an overview of evaluation experiments in information retrieval, and also of statistical approaches to search. A strong connection exists between them: the notion that the objective of search can be expressed in terms of the measures used for evaluation informs the statistical theory in several ways. The latest manifestation of this connection is the work on optimization of ranking algorithms, using machine learning techniques.\",\"PeriodicalId\":287514,\"journal\":{\"name\":\"International Workshop On Research Issues in Digital Libraries\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop On Research Issues in Digital Libraries\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1364742.1364745\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop On Research Issues in Digital Libraries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1364742.1364745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the science of search: statistical approaches, evaluation, optimisation
This paper, based on a talk, presents an overview of evaluation experiments in information retrieval, and also of statistical approaches to search. A strong connection exists between them: the notion that the objective of search can be expressed in terms of the measures used for evaluation informs the statistical theory in several ways. The latest manifestation of this connection is the work on optimization of ranking algorithms, using machine learning techniques.
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