{"title":"自动调节文档长度规范化的约束","authors":"Ronan Cummins, C. O'Riordan","doi":"10.1145/2396761.2398662","DOIUrl":null,"url":null,"abstract":"Retrieval functions in information retrieval (IR) are fundamental to the effectiveness of search systems. However, considerable parameter tuning is often needed to increase the effectiveness of the retrieval. Document length normalisation is one such aspect that requires tuning on a per-query and per-collection basis for many retrieval functions. In this paper, we develop an approach that regularises the level of normalisation to apply on a per-query basis. We formally describe the interaction between query-terms and document length normalisation using a constraint. We then develop a general pre-retrieval approach to adapt a number of state-of-the-art ranking functions so that they adhere to the constraint. Finally, we empirically demonstrate that the adapted retrieval functions outperform default versions of the original retrieval functions, and perform at least comparably to tuned versions of the original functions, on a number of datasets. Essentially this regulates the normalisation parameter in a number of retrieval functions on a per-query basis in a principled manner.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"A constraint to automatically regulate document-length normalisation\",\"authors\":\"Ronan Cummins, C. O'Riordan\",\"doi\":\"10.1145/2396761.2398662\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Retrieval functions in information retrieval (IR) are fundamental to the effectiveness of search systems. However, considerable parameter tuning is often needed to increase the effectiveness of the retrieval. Document length normalisation is one such aspect that requires tuning on a per-query and per-collection basis for many retrieval functions. In this paper, we develop an approach that regularises the level of normalisation to apply on a per-query basis. We formally describe the interaction between query-terms and document length normalisation using a constraint. We then develop a general pre-retrieval approach to adapt a number of state-of-the-art ranking functions so that they adhere to the constraint. Finally, we empirically demonstrate that the adapted retrieval functions outperform default versions of the original retrieval functions, and perform at least comparably to tuned versions of the original functions, on a number of datasets. Essentially this regulates the normalisation parameter in a number of retrieval functions on a per-query basis in a principled manner.\",\"PeriodicalId\":313414,\"journal\":{\"name\":\"Proceedings of the 21st ACM international conference on Information and knowledge management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 21st ACM international conference on Information and knowledge management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2396761.2398662\",\"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 21st ACM international conference on Information and knowledge management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2396761.2398662","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A constraint to automatically regulate document-length normalisation
Retrieval functions in information retrieval (IR) are fundamental to the effectiveness of search systems. However, considerable parameter tuning is often needed to increase the effectiveness of the retrieval. Document length normalisation is one such aspect that requires tuning on a per-query and per-collection basis for many retrieval functions. In this paper, we develop an approach that regularises the level of normalisation to apply on a per-query basis. We formally describe the interaction between query-terms and document length normalisation using a constraint. We then develop a general pre-retrieval approach to adapt a number of state-of-the-art ranking functions so that they adhere to the constraint. Finally, we empirically demonstrate that the adapted retrieval functions outperform default versions of the original retrieval functions, and perform at least comparably to tuned versions of the original functions, on a number of datasets. Essentially this regulates the normalisation parameter in a number of retrieval functions on a per-query basis in a principled manner.