Efficient Batch Processing for Multiple Keyword Queries on Graph Data

L. Chen, C. Liu, X. Yang, B. Wang, Jianxin Li, R. Zhou

    Research output: Chapter in Book/Conference paperConference paper

    1 Citation (Scopus)

    Abstract

    Recently, answering keyword queries on graph data has drawn a great deal of attention from database communities. However, most graph keyword search solutions proposed so far primarily focus on a single query setting. We observe that for a popular keyword query system, the number of keyword queries received could be substantially large even in a short time interval, and the chance that these queries share common keywords is quite high. Therefore, answering keyword queries in batches would significantly enhance the performance of the system. Motivated by this, this paper studies efficient batch processing for multiple keyword queries on graph data. Realized that finding both the optimal query plan for multiple queries and the optimal query plan for a single keyword query on graph data are computationally hard, we first propose two heuristic approaches which target maximizing keyword overlap and give preferences for processing keywords with short sizes. Then we devise a cardinality based cost estimation model that takes both graph data statistics and search semantics into account. Based on the model, we design an A∗ based algorithm to find the global optimal execution plan for multiple queries. We evaluate the proposed model and algorithms on two real datasets and the experimental results demonstrate their efficacy. © 2016 Copyright held by the owner/author(s).
    Original languageEnglish
    Title of host publicationProceedings of the 25th ACM International Conference on Information and Knowledge Management
    EditorsS Mukhopadhyay , C Zhai
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery (ACM)
    Pages1261-1270
    Number of pages10
    ISBN (Print)9781450340731
    DOIs
    Publication statusPublished - 2016
    Event25th ACM International Conference on Information and Knowledge Management (CIKM 2016) - Indianapolis, Indianapolis, United States
    Duration: 24 Oct 201629 Oct 2016

    Conference

    Conference25th ACM International Conference on Information and Knowledge Management (CIKM 2016)
    CountryUnited States
    CityIndianapolis
    Period24/10/1629/10/16

      Fingerprint

    Cite this

    Chen, L., Liu, C., Yang, X., Wang, B., Li, J., & Zhou, R. (2016). Efficient Batch Processing for Multiple Keyword Queries on Graph Data. In S. Mukhopadhyay , & C. Zhai (Eds.), Proceedings of the 25th ACM International Conference on Information and Knowledge Management (pp. 1261-1270). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/2983323.2983806