{"title":"重新访问规范化查询承诺","authors":"Haggai Roitman","doi":"10.1145/3331184.3331334","DOIUrl":null,"url":null,"abstract":"We revisit the Normalized Query Commitment (NQC) query performance prediction (QPP) method. To this end, we suggest a scaled extension to a discriminative QPP framework and use it to analyze NQC. Using this analysis allows us to redesign NQC and suggest several options for improvement.","PeriodicalId":20700,"journal":{"name":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Normalized Query Commitment Revisited\",\"authors\":\"Haggai Roitman\",\"doi\":\"10.1145/3331184.3331334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We revisit the Normalized Query Commitment (NQC) query performance prediction (QPP) method. To this end, we suggest a scaled extension to a discriminative QPP framework and use it to analyze NQC. Using this analysis allows us to redesign NQC and suggest several options for improvement.\",\"PeriodicalId\":20700,\"journal\":{\"name\":\"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3331184.3331334\",\"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 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3331184.3331334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We revisit the Normalized Query Commitment (NQC) query performance prediction (QPP) method. To this end, we suggest a scaled extension to a discriminative QPP framework and use it to analyze NQC. Using this analysis allows us to redesign NQC and suggest several options for improvement.
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