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Efficient query processing for XML keyword queries based on the IDList index

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Abstract

Keyword search over XML data has attracted a lot of research efforts in the last decade, where one of the fundamental research problems is how to efficiently answer a given keyword query w.r.t. a certain query semantics. We found that the key factor resulting in the inefficiency for existing methods is that they all heavily suffer from the common-ancestor-repetition problem. In this paper, we propose a novel form of inverted list, namely the IDList; the IDList for keyword \(k\) consists of ordered nodes that directly or indirectly contain \(k\). We then show that finding keyword query results based on the smallest lowest common ancestor and exclusive lowest common ancestor semantics can be reduced to ordered set intersection problem, which has been heavily optimized due to its application in areas such as information retrieval and database systems. We propose several algorithms that exploit set intersection in different directions and with or without using additional indexes. We further propose several algorithms that are based on hash search to simplify the operation of finding common nodes from all involved IDLists. We have conducted an extensive set of experiments using many state-of-the-art algorithms and several large-scale datasets. The results demonstrate that our proposed methods outperform existing methods by up to two orders of magnitude in many cases.

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Notes

  1. The matched element in \(L_{i}\) to eliminator \(e\) is the minimum element that is equal to or greater than \(e\), if all lists are sorted in ascending order.

  2. http://www.monetdb.org/Home.

  3. http://www.informatik.uni-trier.de/~ley/db/.

  4. http://www.oracle.com/technetwork/products/berkeleydb/overview/index.html.

  5. In Fig. 18, we take the result selectivity of existing methods as that of our method to make a fair comparison.

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Acknowledgments

This research was partially supported by the grants from the Natural Science Foundation of China (No. 61073060, 60833005, 61070055, 91024032, 91124001), the National Science and Technology Major Project (No. 2010-ZX01042-002-003), the Fundamental Research Funds for the Central Univ., the Research Funds of Renmin Univ. (No. 11XNL010, 10XNI018), and the Research Funds from Education Department of Hebei Province (No. Y2012014). Zhifeng Bao’s research is carried out at the SeSaMe Centre. It is supported by the Singapore NRF under its IRC@SG Funding Initiative and administered by the IDMPO. Wei Wang was partially supported by ARC DP130103401 and DP130103405.

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Authors and Affiliations

  1. The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao, China

    Junfeng Zhou & Jinjia Zhao

  2. Interactive Digital Media Institute, Singapore, Singapore

    Zhifeng Bao

  3. The University of New South Wales, Kensington, NSW, Australia

    Wei Wang

  4. Renmin University of China, Beijing, China

    Xiaofeng Meng

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  1. Junfeng Zhou
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  2. Zhifeng Bao
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  3. Wei Wang
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Correspondence to Junfeng Zhou.

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Zhou, J., Bao, Z., Wang, W. et al. Efficient query processing for XML keyword queries based on the IDList index. The VLDB Journal 23, 25–50 (2014). https://doi.org/10.1007/s00778-013-0313-2

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