Split-Lists and Initial Thresholds for WAND-based Search

Split-Lists and Initial Thresholds for WAND-based Search
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基于 WAND 的搜索的拆分列表和初始阈值

DOI:
10.1145/3209978.3210066
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发表时间:
2018
期刊:
The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
影响因子:
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通讯作者:
Frank Wm. Tompa
Frank Wm. Tompa
中科院分区:
--
文献类型:
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作者:
Andrew Kane;Frank Wm. Tompa

文献摘要

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我们研究搜索引擎的排名安全查询执行使用的WAND和国家的最先进的宝马算法的性能。支持广泛的实验,我们提出了两种方法来提高查询性能:初始列表阈值时,k值是大的,我们的分裂列表WAND方法应使用,而不是正常的WAND或宝马方法。我们还建议基于重排序的分布式系统在选择从每个分区返回的结果时使用较小的k值。
We examine search engine performance for rank-safe query execution using the WAND and state-of-the-art BMW algorithms. Supported by extensive experiments, we suggest two approaches to improve query performance: initial list thresholds should be used when k values are large, and our split-list WAND approach should be used instead of the normal WAND or BMW approaches. We also recommend that reranking-based distributed systems use smaller k values when selecting the results to return from each partition.