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Detecting Maximum k-Plex with Iterative Proper ℓ-Plex Search

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Discovery Science (DS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8777))

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Abstract

In this paper, we are concerned with the notion of k-plex, a relaxation model of clique, where degree of relaxation is controlled by the parameter k. Particularly, we present an efficient algorithm for detecting a maximum k-plex in a given simple undirected graph. Existing algorithms for extracting a maximum k-plex do not work well for larger k-values because the number of k-plexes exponentially grows as k becomes larger. In order to design an efficient algorithm for the problem, we introduce a notion of properness of k-plex. Our algorithm tries to iteratively find a maximum proper ℓ-plex, decreasing the value of ℓ from k to 1. At each iteration stage, the maximum size of proper ℓ-plex found so far can work as an effective lower bound which makes our branch-and-bound pruning more powerful. Our experimental results for several benchmark graphs show that our algorithm can detect maximum k-plexes much faster than SPLEX, the existing most efficient algorithm.

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References

  1. Balasundaram, B., Butenko, S., Hicks, I.V.: Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem. Operations Research 59(1), 133–142 (2011), INFORMS

    Google Scholar 

  2. Batagelj, V., Mrvar, A.: Pajek Datasets (2006), http://vlado.fmf.uni-lj.si/pub/networks/data/

  3. Brunato, M., Hoos, H.H., Battiti, R.: On Effectively Finding Maximal Quasi-cliques in Graphs. In: Maniezzo, V., Battiti, R., Watson, J.-P. (eds.) LION 2007 II. LNCS (LNAI), vol. 5313, pp. 41–55. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  4. Eppstein, D., Strash, D.: Listing All Maximal Cliques in Large Sparse Real-World Graphs. In: Pardalos, P.M., Rebennack, S. (eds.) SEA 2011. LNCS, vol. 6630, pp. 364–375. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Grossman, J., Ion, P., Castro, R.D.: The Erdös Number Project (2007), http://www.oakland.edu/enp/

  6. Matsudaira, M., Haraguchi, M., Okubo, Y., Tomita, E.: An Algorithm for Enumerating Maximal j-Cored Connected k-Plexes. In: Proc. of the 28th Annual Conf. of the Japanese Society for Artificial Intelligence, 3J3-1 (2014) (in Japanese)

    Google Scholar 

  7. Matsudaira, M.: A Branch-and-Bound Algorithm for Enumerating Maximal j-Cored k-Plexes, Master Thesis, Graduate School of Information Science and Technology, Hokkaido University (2014) (in Japanese)

    Google Scholar 

  8. McClosky, B., Hicks, I.V.: Combinatorial Algorithms for The Maximum k-Plex Problem. Journal of Combinatorial Optimization 23(1), 29–49 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  9. Moser, H., Niedermeier, R., Sorge, M.: Exact Combinatorial Algorithms and Experiments for Finding Maximum k-Plexes. Journal of Combinatorial Optimization 24(3), 347–373 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  10. Östergård, P.R.J.: A Fast Algorithm for the Maximum Clique Problem. Discrete Applied Mathematics 120(1-3), 197–207 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Pattillo, J., Youssef, N., Butenko, S.: Clique Relaxation Models in Social Network Analysis. In: Thai, M.T., Pardalos, P.M. (eds.) Handbook of Optimization in Complex Networks: Communication and Social Networks, Springer Optimization and Its Applications, vol. 58, pp. 143–162 (2012)

    Google Scholar 

  12. Scott, J.P., Carrington, P.J. (eds.): The SAGE Handbook of Social Network Analysis. Sage (2011)

    Google Scholar 

  13. Seidman, S.B., Foster, B.L.: A Graph Theoretic Generalization of the Clique Concept. Journal of Mathematical Sociology 6, 139–154 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  14. Tomita, E., Nakanishi, H.: Polynomial-Time Solvability of the Maximum Clique Problem. In: Proc. of the European Computing Conference - ECC 2009 and the 3rd Int���l Conf. on Computational Intelligence - CI 2009, pp. 203–208 (2009)

    Google Scholar 

  15. Tomita, E., Kameda, T.: An Efficient Branch-and-Bound Algorithm for Finding a Maximum Clique with Computational Experiments. Journal of Global Optimization 37(1), 95–111 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  16. Tomita, E., Tanaka, A., Takahashi, H.: The Worst-Case Time Complexity for Generating All Maximal Cliques and Computational Experiments. Theoretical Computer Science 363(1), 28–42 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  17. Uno, T.: An Efficient Algorithm for Solving Pseudo Clique Enumeration Problem. Algorithmica 56, 3–16 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  18. Wu, B., Pei, X.: A Parallel Algorithm for Enumerating All the Maximal k-Plexes. In: Washio, T., et al. (eds.) PAKDD 2007. LNCS (LNAI), vol. 4819, pp. 476–483. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

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Okubo, Y., Matsudaira, M., Haraguchi, M. (2014). Detecting Maximum k-Plex with Iterative Proper ℓ-Plex Search. In: Džeroski, S., Panov, P., Kocev, D., Todorovski, L. (eds) Discovery Science. DS 2014. Lecture Notes in Computer Science(), vol 8777. Springer, Cham. https://doi.org/10.1007/978-3-319-11812-3_21

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  • DOI: https://doi.org/10.1007/978-3-319-11812-3_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11811-6

  • Online ISBN: 978-3-319-11812-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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