Abstract
Subgraph isomorphism search is a fundamental problem in querying graph-like structured data. It consists to enumerate the subgraphs of a data graph that match a query graph. It is an NP-complete problem that knows several investigations. Most of them extend Ullmann’s backtracking algorithm and rely on filtering and pruning mechanisms to reduce the search space. Most of these solutions focus on how to alleviate the searching step of the algorithm, identified as the most costly part, with various techniques and data structures. However, little effort is devoted to reduce the cost of the filtering step. In this paper, we take a completely different approach that relies on a constant time pruning mechanism while keeping Ullman’s backtracking subgraph search subroutine. The main idea is to aggregate the semantic and topological information that surround a vertex into a simple integer. This simple neighbourhood encoding reduces the time complexity of vertex filtering from cubic to quadratic. We evaluate our approach on several real-word datasets and compare it with the state of the art algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The source code of the two algorithms is available on Git and will be provided.
- 2.
Stanford Network Analysis Platform. http://snap.stanford.edu/.
- 3.
References
Bhattarai, B., Liu, H., Huang, H.H.: CECI: compact embedding cluster index for scalable subgraph matching. In: Proceedings of the 2019 International Conference on Management of Data, SIGMOD 2019, pp. 1447–1462. Association for Computing Machinery, New York (2019). https://doi.org/10.1145/3299869.3300086
Bi, F., Chang, L., Lin, X., Qin, L., Zhang, W.: Efficient subgraph matching by postponing cartesian products. In: Proceedings of the 2016 International Conference on Management of Data, SIGMOD 2016, pp. 1199–1214 (2016)
Bonnici, V., Giugno, R., Pulvirenti, A., Shasha, D., Ferro, A.: A subgraph isomorphism algorithm and its application to biochemical data. BMC Bioinform. 14(Suppl 7), S13 (2013)
Carletti, V., Foggia, P., Saggese, A., Vento, M.: Challenging the time complexity of exact subgraph isomorphism for huge and dense graphs with VF3. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 804–818 (2018). https://doi.org/10.1109/TPAMI.2017.2696940
Cordella, L.P., Foggia, P., Sansone, C., Vento, M.: A (sub)graph isomorphism algorithm for matching large graphs. IEEE Trans. Pattern Anal. Mach. Intell. 26, 1367–1372 (2004)
Han, M., Kim, H., Gu, G., Park, K., Han, W.S.: Efficient subgraph matching: harmonizing dynamic programming, adaptive matching order, and failing set together. In: Proceedings of the 2019 International Conference on Management of Data, SIGMOD 2019, pp. 1429–1446. Association for Computing Machinery, New York (2019). https://doi.org/10.1145/3299869.3319880
Han, W.S., Lee, J., Lee, J.H.: Turboiso: towards ultrafast and robust subgraph isomorphism search in large graph databases. In: ACM SIGMOD International Conference on Management of Data, pp. 337–348. SIGMOD 2013 (2013)
He, H., Singh, A.K.: Graphs-at-a-time: query language and access methods for graph databases. In: ACM SIGMOD International Conference on Management of Data, SIGMOD 2008, pp. 405–418 (2008)
Katsarou, F., Ntarmoset, N., Triantafillou, P.: Subgraph querying with parallel use of query rewritings and alternative algorithms. In: EDBT (2017)
Kim, H., Choi, Y., Park, K., Lin, X., Hong, S.H., Han, W.S.: Versatile equivalences: speeding up subgraph query processing and subgraph matching. In: Proceedings of the 2021 International Conference on Management of Data, SIGMOD 2021, pp. 925–937 (2021). https://doi.org/10.1145/3448016.3457265
Lee, J., Han, W.S., Kasperovics, R., Lee, J.H.: An in-depth comparison of subgraph isomorphism algorithms in graph databases. In: 39th International Conference on Very Large Data Bases, pp. 133–144 (2013)
Ren, X., Wang, J.: Exploiting vertex relationships in speeding up subgraph isomorphism over large graphs. Proc. VLDB Endow. 8(5), 617–628 (2015)
Shang, H., Zhang, Y., Lin, X., Yu, J.X.: Taming verification hardness: an efficient algorithm for testing subgraph isomorphism. Proc. VLDB Endow. 1(1), 364–375 (2008)
Stein, S.K.: Mathematics: The Man-Made Universe. McGraw-Hill, New York (1999). Dover Publications; 3rd Revised edn. (21 March 2013)
Ullmann, J.R.: An algorithm for subgraph isomorphism. J. ACM 23(1), 31–42 (1976)
Zeng, L., Jiang, Y., Lu, W., Zou, L.: Deep analysis on subgraph isomorphism (2021)
Zhang, S., Li, S., Yang, J.: GADDI: distance index based subgraph matching in biological networks. In: EDBT 2009, pp. 192–203 (2009)
Zhao, P., Han, J.: On graph query optimization in large networks. PVLDB 3(1), 340–351 (2010)
Zhu, G., Lin, X., Zhu, K., Zhang, W., Yu, J.X.: TreeSpan efficiently computing similarity all-matching. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD 2012, pp. 529–540 (2012)
Acknowledgements
This work is funded by the French National Research Agency under grant ANR-20-CE23-0002 and INFO-Bourg department, IUT Lyon 1.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Nabti, C.E., Mecharnia, T., Boukhetta, S.E., Amrouche, K., Seba, H. (2023). A Neighborhood Encoding for Subgraph Queries in Graph Databases. In: Strauss, C., Amagasa, T., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2023. Lecture Notes in Computer Science, vol 14146. Springer, Cham. https://doi.org/10.1007/978-3-031-39847-6_30
Download citation
DOI: https://doi.org/10.1007/978-3-031-39847-6_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-39846-9
Online ISBN: 978-3-031-39847-6
eBook Packages: Computer ScienceComputer Science (R0)