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Enumerating Connected Induced Subgraphs: Improved Delay and Experimental Comparison

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SOFSEM 2019: Theory and Practice of Computer Science (SOFSEM 2019)

Abstract

We consider the problem of enumerating all connected induced subgraphs of order k in an undirected graph \(G=(V,E)\). Our main results are two enumeration algorithms with a delay of \(\mathcal {O}(k^2\varDelta )\) where \(\varDelta \) is the maximum degree in the input graph. This improves upon a previous delay bound [Elbassioni, JGAA 2015] for this problem. In addition, we give improved worst-case running time bounds and delay bounds for several known algorithms and perform an experimental comparison of these algorithms for \(k\le 10\) and \(k\ge |V|-3\).

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Notes

  1. 1.

    The source code of our program Enucon is available at www.uni-marburg.de/fb12/arbeitsgruppen/algorithmik/software/.

References

  1. Avis, D., Fukuda, K.: Reverse search for enumeration. Discret. Appl. Math. 65(1–3), 21–46 (1996)

    Article  MathSciNet  Google Scholar 

  2. Bader, D.A., Meyerhenke, H., Sanders, P., Schulz, C., Kappes, A., Wagner, D.: Benchmarking for graph clustering and partitioning. In: Alhajj, R., Rokne, J. (eds.) Encyclopedia of Social Network Analysis and Mining, pp. 73–82. Springer, New York (2014). https://doi.org/10.1007/978-1-4614-6170-8_23

    Chapter  Google Scholar 

  3. Bollobás, B.: The Art of Mathematics - Coffee Time in Memphis. Cambridge University Press, Cambridge (2006)

    Book  Google Scholar 

  4. Elbassioni, K.M.: A polynomial delay algorithm for generating connected induced subgraphs of a given cardinality. J. Graph Algorithms Appl. 19(1), 273–280 (2015)

    Article  MathSciNet  Google Scholar 

  5. Elbassuoni, S., Blanco, R.: Keyword search over RDF graphs. In: Proceedings of the 20th ACM Conference on Information and Knowledge Management, (CIKM 2011), pp. 237–242. ACM (2011)

    Google Scholar 

  6. Kashani, Z.R.M., et al.: Kavosh: a new algorithm for finding network motifs. BMC Bioinform. 10, 318 (2009)

    Article  Google Scholar 

  7. Komusiewicz, C., Sorge, M.: Finding dense subgraphs of sparse graphs. In: Thilikos, D.M., Woeginger, G.J. (eds.) IPEC 2012. LNCS, vol. 7535, pp. 242–251. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33293-7_23

    Chapter  Google Scholar 

  8. Komusiewicz, C., Sorge, M.: An algorithmic framework for fixed-cardinality optimization in sparse graphs applied to dense subgraph problems. Discret. Appl. Math. 193, 145–161 (2015)

    Article  MathSciNet  Google Scholar 

  9. Komusiewicz, C., Sorge, M., Stahl, K.: Finding connected subgraphs of fixed minimum density: implementation and experiments. In: Bampis, E. (ed.) SEA 2015. LNCS, vol. 9125, pp. 82–93. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20086-6_7

    Chapter  Google Scholar 

  10. Kunegis, J.: KONECT: the Koblenz network collection. In: Proceedings of the 22nd International World Wide Web Conference (WWW 2013), pp. 1343–1350. International World Wide Web Conferences Steering Committee/ACM (2013)

    Google Scholar 

  11. Maxwell, S., Chance, M.R., Koyutürk, M.: Efficiently enumerating all connected induced subgraphs of a large molecular network. In: Dediu, A.-H., Martín-Vide, C., Truthe, B. (eds.) AlCoB 2014. LNCS, vol. 8542, pp. 171–182. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07953-0_14

    Chapter  Google Scholar 

  12. Rossi, R.A., Ahmed, N.K.: The network data repository with interactive graph analytics and visualization. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 4292–4293. AAAI Press (2015). http://networkrepository.com

  13. Wernicke, S.: A faster algorithm for detecting network motifs. In: Casadio, R., Myers, G. (eds.) WABI 2005. LNCS, vol. 3692, pp. 165–177. Springer, Heidelberg (2005). https://doi.org/10.1007/11557067_14

    Chapter  Google Scholar 

  14. Wernicke, S.: Combinatorial algorithms to cope with the complexity of biological networks. Ph.D. thesis, Friedrich Schiller University of Jena (2006). http://d-nb.info/982598882

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Correspondence to Frank Sommer .

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Komusiewicz, C., Sommer, F. (2019). Enumerating Connected Induced Subgraphs: Improved Delay and Experimental Comparison. In: Catania, B., Královič, R., Nawrocki, J., Pighizzini, G. (eds) SOFSEM 2019: Theory and Practice of Computer Science. SOFSEM 2019. Lecture Notes in Computer Science(), vol 11376. Springer, Cham. https://doi.org/10.1007/978-3-030-10801-4_22

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  • DOI: https://doi.org/10.1007/978-3-030-10801-4_22

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  • Print ISBN: 978-3-030-10800-7

  • Online ISBN: 978-3-030-10801-4

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