Abstract
Graph and graph database are widely used in many domains, and the graph querying attracts more and more attentions. Among these querying problems, subgraph querying is the most compelling one, since it contains very expensive subgraph isomorphism. The paper proposes a novel subgraph querying method PLGCoding, which use some information of shortest paths and Laplacian spectra to filter out false positives. Specifically, we first extract some features, including some information of vertices, edges, the shortest paths and Laplacian spectra, and encode extracted features. An index PLGCode-Tree is built based on codes to shrink the candidate set. Then, we propose two-step filtering strategy to implement the filtering-and-verification framework and thus generate the answer set. Compared with competing methods on real dataset, experimental results show PLGCoding can improve the querying efficiency.
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Acknowledgements
The research presented in this paper is supported in part by the National Natural Science Foundation of China (Nos. 61602374, 61602376, 61702411), the Natural Science Foundation of Shaanxi Province (CN) (Nos. 2016JQ6041, 2017JQ6020), the Natural Science Foundation of Shaanxi Provincial Department of Education (CN) (Nos. 16JK1552, 16JK1573), and the Foundation of Xi’an University of Technology (No. 112-451115002).
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Zhu, L., Yao, Y., Wang, Y. et al. A novel subgraph querying method based on paths and spectra. Neural Comput & Applic 31, 5671–5678 (2019). https://doi.org/10.1007/s00521-018-3837-y
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DOI: https://doi.org/10.1007/s00521-018-3837-y