Abstract
The Edge Clique Cover (ECC) problem is concerned with covering edges of a graph with the minimum number of cliques, which is an NP-hard problem. This problem has many real-life applications, such as, in computational biology, food science, efficient representation of pairwise information, and so on. In this work we propose using a compact representation of network data based on sparse matrix data structures. Building upon an existing ECC heuristic due to Kellerman we proffer adding vertices during the clique-growing step of the algorithm in judiciously chosen degree-based orders. On a set of standard benchmark instances our ordered approach produced smaller sized clique cover compared to unordered processing.
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We thank referees for their many valuable suggestions that helped improve the paper. This research was partially supported by the Natural Sciences and Engineering Research Council (NSERC) under Discovery Grants Program.
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Abdullah, W.M., Hossain, S., Khan, M.A. (2021). Covering Large Complex Networks by Cliques—A Sparse Matrix Approach. In: Kilgour, D.M., Kunze, H., Makarov, R., Melnik, R., Wang, X. (eds) Recent Developments in Mathematical, Statistical and Computational Sciences. AMMCS 2019. Springer Proceedings in Mathematics & Statistics, vol 343. Springer, Cham. https://doi.org/10.1007/978-3-030-63591-6_11
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