{"title":"按时间排序查询处理","authors":"Ahmed Elbagoury, Matt Crane, Jimmy J. Lin","doi":"10.1145/2970398.2970434","DOIUrl":null,"url":null,"abstract":"Query processing strategies for ranked retrieval have been studied for decades. In this paper we propose a new strategy, which we call rank-at-a-time query processing, that evaluates documents in descending order of quantized scores and is able to directly compute the final document ranking via a sequence of boolean intersections. We show that such a strategy is equivalent to a second-order restricted composition of per-term scores. Rank-at-a-time query processing has the advantage that it is anytime score-safe, which means that the retrieval algorithm can self-adapt to produce an exact ranking given an arbitrary latency constraint. Due to the combinatorial nature of compositions, however, a naive implementation is too slow to be of practical use. To address this issue, we introduce a hybrid variant that is able to reduce query latency to a point that is on par with state-of-the-art retrieval engines.","PeriodicalId":443715,"journal":{"name":"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Rank-at-a-Time Query Processing\",\"authors\":\"Ahmed Elbagoury, Matt Crane, Jimmy J. Lin\",\"doi\":\"10.1145/2970398.2970434\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Query processing strategies for ranked retrieval have been studied for decades. In this paper we propose a new strategy, which we call rank-at-a-time query processing, that evaluates documents in descending order of quantized scores and is able to directly compute the final document ranking via a sequence of boolean intersections. We show that such a strategy is equivalent to a second-order restricted composition of per-term scores. Rank-at-a-time query processing has the advantage that it is anytime score-safe, which means that the retrieval algorithm can self-adapt to produce an exact ranking given an arbitrary latency constraint. Due to the combinatorial nature of compositions, however, a naive implementation is too slow to be of practical use. To address this issue, we introduce a hybrid variant that is able to reduce query latency to a point that is on par with state-of-the-art retrieval engines.\",\"PeriodicalId\":443715,\"journal\":{\"name\":\"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2970398.2970434\",\"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 2016 ACM International Conference on the Theory of Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2970398.2970434","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Query processing strategies for ranked retrieval have been studied for decades. In this paper we propose a new strategy, which we call rank-at-a-time query processing, that evaluates documents in descending order of quantized scores and is able to directly compute the final document ranking via a sequence of boolean intersections. We show that such a strategy is equivalent to a second-order restricted composition of per-term scores. Rank-at-a-time query processing has the advantage that it is anytime score-safe, which means that the retrieval algorithm can self-adapt to produce an exact ranking given an arbitrary latency constraint. Due to the combinatorial nature of compositions, however, a naive implementation is too slow to be of practical use. To address this issue, we introduce a hybrid variant that is able to reduce query latency to a point that is on par with state-of-the-art retrieval engines.