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A query refinement framework for xml keyword search

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Abstract

Existing work of XML keyword search focus on how to find relevant and meaningful data fragments for a query, assuming each keyword is intended as part of it. However, in XML keyword search, user queries usually contain irrelevant or mismatched terms, typos etc, which may easily lead to empty or meaningless results. In this paper, we introduce the problem of content-aware XML keyword query refinement, where the search engine should judiciously decide whether a user query Q needs to be refined during the processing of Q, and find a list of promising refined query candidates which guarantee to have meaningful matching results over the XML data, without any user interaction or a second try. To achieve this goal, we build a novel content-aware XML keyword query refinement framework consisting of two core parts: (1) we build a query ranking model to evaluate the quality of a refined query RQ, which captures the morphological/semantical similarity between Q and RQ and the dependency of keywords of RQ over the XML data; (2) we integrate the exploration of RQ candidates and the generation of their matching results as a single problem, which is fulfilled within a one-time scan of the related keyword inverted lists optimally. Finally, an extensive empirical study verifies the efficiency and effectiveness of our framework.

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Notes

  1. Basically, it considers a node type t in the DTD of XML data as an entity if t is “*”-annotated in its DTD. However, it may cause the multi-valued attribute to be mistakenly identified as an entity, thus it usually requires the verification and decision from database administrators.

  2. Without ambiguity caused, we use “refinement rule” instead of “refinement rule instance” in the rest of the paper.

  3. To facilitate our discussion, the dissimilarity score of a single term deletion rule is 2 throughout all examples in this paper.

  4. http://www.ibiblio.org/xml/books/biblegold/examples/baseball/

  5. The url is anonymized due to double blind review policy

  6. To facilitate the discussion, we call our refinement approach as XRefine in the rest of the paper.

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Acknowledgments

This work is partially supported by the Australian Research Council’s Discovery Projects Scheme (DP170102726), the National Natural Foundation of China under Grant No. 91646204 and the JSPS KAKENHI Grant No. 16K16058.

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Authors and Affiliations

  1. Computer Science and IT, RMIT University, Melbourne, Australia

    Zhifeng Bao

  2. National Institute of Informatics, Tokyo, Japan

    Yi Yu

  3. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

    Jian Shen & Zhangjie Fu

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  1. Zhifeng Bao
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  2. Yi Yu
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  3. Jian Shen
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  4. Zhangjie Fu
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Correspondence to Zhifeng Bao.

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Bao, Z., Yu, Y., Shen, J. et al. A query refinement framework for xml keyword search. World Wide Web 20, 1469–1505 (2017). https://doi.org/10.1007/s11280-017-0447-z

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