Improving Dynamic Index Pruning via Linear Programming

Simon Jonassen
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Abstract

Dynamic index pruning techniques are commonly used to speed up query processing in Web search engines. In this work, we propose a linear programming technique which can further improve the performance of the state-of-the-art dynamic index pruning techniques. The experiments we conducted demonstrate that the proposed technique achieves reduction in terms of the disk access, index decompression, and scoring costs compared to the well-known Max-Score technique.
基于线性规划的动态索引剪枝算法
动态索引修剪技术通常用于加快Web搜索引擎中的查询处理速度。在这项工作中,我们提出了一种线性规划技术,可以进一步提高最先进的动态索引修剪技术的性能。我们进行的实验表明,与众所周知的Max-Score技术相比,所提出的技术在磁盘访问、索引解压缩和评分成本方面实现了降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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