文档排序索引上的任意时间排名
Anytime Ranking on Document-Ordered Indexes
摘要：
倒排索引仍然是文本搜索引擎的支柱，它允许对大型文档集合进行高效查询。虽然有许多可能的组织，但文档排序索引是最常见的，因为它们适用于各种查询类型，支持索引更新，并允许有效的动态修剪操作。文档排序索引的一个缺点是，高分文档可能分布在文档标识符空间中，这意味着提前终止的索引遍历算法可能会使搜索效率处于危险之中。另一种选择是影响排序索引，它主要支持top-k析取，但也允许随时查询处理，其中搜索可以随时终止，搜索质量随着处理延迟的增加而提高。随时查询处理可用于有效地减少高百分位数尾部延迟，这对于服务级别协议（SLA）强加响应时间要求的操作场景是必不可少的。在这项工作中，我们将展示如何组织文档排序的索引，使他们可以在任何时候查询的方式，使严格的延迟控制与有效的提前终止。我们的实验表明，处理文档排序的主题段选择一个简单的分数估计优于现有的任何时候的算法，并允许查询运行时间被准确地限制，以符合SLA的要求。
英文摘要：
Inverted indexes continue to be a mainstay of text search engines, allowing efficient querying of large document collections. While there are a number of possible organizations, document-ordered indexes are the most common, since they are amenable to various query types, support index updates, and allow for efficient dynamic pruning operations. One disadvantage with document-ordered indexes is that high-scoring documents can be distributed across the document identifier space, meaning that index traversal algorithms that terminate early might put search effectiveness at risk. The alternative is impact-ordered indexes, which primarily support top-k disjunctions, but also allow for anytime query processing, where the search can be terminated at any time, with search quality improving as processing latency increases. Anytime query processing can be used to effectively reduce high-percentile tail latency which is essential for operational scenarios in which a service level agreement (SLA) imposes response time requirements. In this work, we show how document-ordered indexes can be organized such that they can be queried in an anytime fashion, enabling strict latency control with effective early termination. Our experiments show that processing document-ordered topical segments selected by a simple score estimator outperforms existing anytime algorithms, and allows query runtimes to be accurately limited in order to comply with SLA requirements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
