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Improving the Time and Space Performance for Processing Keyword Queries on XML Databases

机译:改进在XML数据库上处理关键字查询的时间和空间性能

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摘要

For an XML database, it is important to automatically reason meaningful answers for a given keyword query. Particularly, the MaxMatch algorithm is proposed to output contributors, which represent more (or equal number of) keywords than those contained by their sibling nodes. Such concept can distinguish the importance of sibling nodes and has attracted a lot of attention. In this paper, we intend to improve the time and space performance of the original approach. We first propose the LevelPrune algorithm, which only needs to construct the smallest necessary intermediate tree and can also reduce the times of processing nodes. We then extend the idea of constructing trees level by level to optimize physical representations, and design the corresponding algorithm LevelPrune. According to the experimental results, our proposed algorithms outperform other stateof-the-art approaches by an order of magnitude in some cases. Moreover, the index size of LevelPrune. is significantly reduced compared with that of the original approach.
机译:对于XML数据库,对于给定的关键字查询自动推理有意义的答案很重要。特别是,提出了MaxMatch算法来输出贡献者,这些贡献者表示比其同级节点所包含的关键词更多(或相等数量)的关键词。这种概念可以区分同级节点的重要性,并引起了很多关注。在本文中,我们打算改善原始方法的时空性能。我们首先提出LevelPrune算法,该算法只需要构造最小的必要中间树,还可以减少处理节点的时间。然后,我们扩展了逐级构造树以优化物理表示的想法,并设计了相应的算法LevelPrune。根据实验结果,在某些情况下,我们提出的算法要比其他现有方法高出一个数量级。此外,LevelPrune的索引大小。与原始方法相比,该方法明显减少了。

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