Fast Disjunctive Candidate Generation Using Live Block Filtering
Fast Disjunctive Candidate Generation Using Live Block Filtering
复制标题
使用实时块过滤快速生成析取候选
DOI：
10.1145/3437963.3441813
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Torsten Suel
中科院分区：
文献类型：
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作者：
Antonio Mallia;Michal Siedlaczek;Torsten Suel
大量的研究集中在搜索引擎查询处理的效率上，特别是在返回包含至少一个查询词的最高得分k个结果的析取top-k查询上。简单排名函数上的析取top-k查询通常用于检索候选结果的初始集合，然后由更复杂的，通常是机器学习的排名器重新排名。许多优化的top-k算法已经被提出，包括MaxScore，WAND，BMW和JASS。虽然最快的方法在top-10和top-100查询上取得了令人印象深刻的结果，但对于通常用于候选生成的较大k，它们往往会变得慢得多。在本文中，我们专注于大k的析取top-k查询。我们提出了新的算法，实现更快的查询处理的k值高达数千或数万。我们的算法建立在Dimopoulos等人的实时块过滤方法之上，并利用现代CPU的SIMD功能。我们还对我们的方法与已知最快的方法进行了详细的实验比较，并发布了我们的方法和底层live-block机制的完整模型实现，这将允许其他人在live-block方法下设计和实验其他方法。
A lot of research has focused on the efficiency of search engine query processing, and in particular on disjunctive top-k queries that return the highest scoring k results that contain at least one of the query terms. Disjunctive top-k queries over simple ranking functions are commonly used to retrieve an initial set of candidate results that are then reranked by more complex, often machine-learned rankers. Many optimized top-k algorithms have been proposed, including MaxScore, WAND, BMW, and JASS. While the fastest methods achieve impressive results on top-10 and top-100 queries, they tend to become much slower for the larger k commonly used for candidate generation. In this paper, we focus on disjunctive top-k queries for larger k. We propose new algorithms that achieve much faster query processing for values of k up to thousands or tens of thousands. Our algorithms build on top of the live-block filtering approach of Dimopoulos et al, and exploit the SIMD capabilities of modern CPUs. We also perform a detailed experimental comparison of our methods with the fastest known approaches, and release a full model implementation of our methods and of the underlying live-block mechanism, which will allows others to design and experiment with additional methods under the live-block approach.
速度更快的 BlockMax WAND，跳跃时间更长
DOI：
10.1007/978-3-030-15712-8_52
发表时间：
2019
期刊：
European Conference on Information Retrieval
影响因子：
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作者：
Mallia, Antonio;Porciani, Elia
通讯作者：
Porciani, Elia
PISA：学术界表现指数和搜索
DOI：
--
发表时间：
2019
期刊：
Proceedings of the Open-Source IR Replicability Challenge
影响因子：
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作者：
Mallia, Antonio;Siedlaczek, Michal;Mackenzie, Joel;Suel, Torsten
通讯作者：
Suel, Torsten