Abstract
The partial evaluation and assembly framework has recently been applied for processing subgraph matching queries over large-scale knowledge graphs in the distributed environment. The framework is implemented on the master-slave architecture, endowed with outstanding scalability. However, there exists a drawback of partial evaluation, that if the volume of intermediate results is large, assembly computation which is handled by the master would be a bottleneck. In this paper, we propose an efficient assembly algorithm by exploring the characteristics of intermediate results generated during the partial matching stage in each fragment. (1) The partial matching index (PM-Index) structure are constructed by utilizing the incoming and outgoing vertices in parallel to improve the searching efficiency of the assembling phase. (2) The time and space complexity of PM-Index construction are analysed. (3) The experimental results over benchmark datasets show that our approach outperforms the state-of-the-art methods.
J. Xing and B. Liu—These authors contributed equally to this work and should be considered co-first authors.
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Acknowledgments
This work is supported by the National Key Research and Development Program of China (2019YFE0198600) and National Natural Science Foundation of China (61972275), partially supported by Australian Research Council Linkage Project (LP180100750).
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Xing, J., Liu, B., Li, J., Choudhury, F.M., Wang, X. (2021). Optimal Subgraph Matching Queries over Distributed Knowledge Graphs Based on Partial Evaluation. In: Zhang, W., Zou, L., Maamar, Z., Chen, L. (eds) Web Information Systems Engineering – WISE 2021. WISE 2021. Lecture Notes in Computer Science(), vol 13080. Springer, Cham. https://doi.org/10.1007/978-3-030-90888-1_22
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