A Parameterized Complexity View on Collapsing k-Cores

Authors Junjie Luo, Hendrik Molter, Ondrej Suchý



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Author Details

Junjie Luo
  • Algorithmics and Computational Complexity, Faculty IV, TU Berlin, Berlin, Germany, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China , School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China
Hendrik Molter
  • Algorithmics and Computational Complexity, Faculty IV, TU Berlin, Berlin, Germany
Ondrej Suchý
  • Department of Theoretical Computer Science, Faculty of Information Technology, Czech Technical University in Prague, Prague, Czech Republic

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Junjie Luo, Hendrik Molter, and Ondrej Suchý. A Parameterized Complexity View on Collapsing k-Cores. In 13th International Symposium on Parameterized and Exact Computation (IPEC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 115, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.IPEC.2018.7

Abstract

We study the NP-hard graph problem Collapsed k-Core where, given an undirected graph G and integers b, x, and k, we are asked to remove b vertices such that the k-core of remaining graph, that is, the (uniquely determined) largest induced subgraph with minimum degree k, has size at most x. Collapsed k-Core was introduced by Zhang et al. [AAAI 2017] and it is motivated by the study of engagement behavior of users in a social network and measuring the resilience of a network against user drop outs. Collapsed k-Core is a generalization of r-Degenerate Vertex Deletion (which is known to be NP-hard for all r >=0) where, given an undirected graph G and integers b and r, we are asked to remove b vertices such that the remaining graph is r-degenerate, that is, every its subgraph has minimum degree at most r. 
We investigate the parameterized complexity of Collapsed k-Core with respect to the parameters b, x, and k, and several structural parameters of the input graph. We reveal a dichotomy in the computational complexity of Collapsed k-Core for k <=2 and k >= 3. For the latter case it is known that for all x >= 0 Collapsed k-Core is W[P]-hard when parameterized by b. We show that Collapsed k-Core is W[1]-hard when parameterized by b and in FPT when parameterized by (b+x) if k <=2. Furthermore, we show that Collapsed k-Core is in FPT when parameterized by the treewidth of the input graph and presumably does not admit a polynomial kernel when parameterized by the vertex cover number of the input graph.

Subject Classification

ACM Subject Classification
  • Theory of computation → Graph algorithms analysis
  • Theory of computation → Parameterized complexity and exact algorithms
Keywords
  • r-Degenerate Vertex Deletion
  • Feedback Vertex Set
  • Fixed-Parameter Tractability
  • Kernelization Lower Bounds
  • Graph Algorithms
  • Social Network Analysis

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References

  1. Karl A. Abrahamson, Rodney G. Downey, and Michael R. Fellows. Fixed-parameter tractability and completeness IV: On completeness for W[P] and PSPACE analogues. Annals of Pure and Applied Logic, 73(3):235-276, 1995. Google Scholar
  2. Kshipra Bhawalkar, Jon Kleinberg, Kevin Lewi, Tim Roughgarden, and Aneesh Sharma. Preventing unraveling in social networks: the anchored k-core problem. SIAM Journal on Discrete Mathematics, 29(3):1452-1475, 2015. Google Scholar
  3. Hans L. Bodlaender, Pål Grønås Drange, Markus S. Dregi, Fedor V. Fomin, Daniel Lokshtanov, and Michał Pilipczuk. A c^k n 5-Approximation Algorithm for Treewidth. SIAM Journal on Computing, 45(2):317-378, 2016. Google Scholar
  4. Hans L Bodlaender, Bart MP Jansen, and Stefan Kratsch. Kernelization lower bounds by cross-composition. SIAM Journal on Discrete Mathematics, 28(1):277-305, 2014. Google Scholar
  5. Yixin Cao. A Naive Algorithm for Feedback Vertex Set. In Proceedings of the 1st Symposium on Simplicity in Algorithms, (SOSA '18), volume 61 of OASICS, pages 1:1-1:9. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2018. Google Scholar
  6. Yixin Cao, Jianer Chen, and Yang Liu. On feedback vertex set: New measure and new structures. Algorithmica, 73(1):63-86, 2015. Google Scholar
  7. Rajesh Chitnis, Fedor V. Fomin, and Petr A. Golovach. Parameterized complexity of the anchored k-core problem for directed graphs. Information and Computation, 247:11-22, 2016. Google Scholar
  8. Rajesh Hemant Chitnis, Fedor V. Fomin, and Petr A. Golovach. Preventing Unraveling in Social Networks Gets Harder. In Proceedins of the 27th AAAI Conference on Artificial Intelligence (AAAI '13), pages 1085-1091. AAAI Press, 2013. Google Scholar
  9. Marek Cygan, Fedor V. Fomin, Łukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, and Saket Saurabh. Parameterized Algorithms. Springer, 2015. Google Scholar
  10. Reinhard Diestel. Graph Theory, 5th Edition, volume 173 of Graduate Texts in Mathematics. Springer, 2016. Google Scholar
  11. David Garcia, Pavlin Mavrodiev, and Frank Schweitzer. Social resilience in online communities: The autopsy of friendster. In Proceedings of the 1st ACM Conference on Online Social Networks (COSN '13), pages 39-50. ACM, 2013. Google Scholar
  12. Michael R. Garey and David S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, 1979. Google Scholar
  13. Jiong Guo, Jens Gramm, Falk Hüffner, Rolf Niedermeier, and Sebastian Wernicke. Compression-based fixed-parameter algorithms for feedback vertex set and edge bipartization. Journal of Computer and System Sciences, 72(8):1386-1396, 2006. Google Scholar
  14. Yoichi Iwata. Linear-Time Kernelization for Feedback Vertex Set. In Ioannis Chatzigiannakis, Piotr Indyk, Fabian Kuhn, and Anca Muscholl, editors, 44th International Colloquium on Automata, Languages, and Programming (ICALP 2017), volume 80 of Leibniz International Proceedings in Informatics (LIPIcs), pages 68:1-68:14, Dagstuhl, Germany, 2017. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. URL: http://dx.doi.org/10.4230/LIPIcs.ICALP.2017.68.
  15. Ton Kloks. Treewidth, Computations and Approximations, volume 842 of Lecture Notes in Computer Science. Springer, 1994. Google Scholar
  16. Tomasz Kociumaka and Marcin Pilipczuk. Faster deterministic feedback vertex set. Information Processing Letters, 114(10):556-560, 2014. Google Scholar
  17. Daniel Lokshtanov, MS Ramanujan, and Saket Saurabh. Linear Time Parameterized Algorithms for Subset Feedback Vertex Set. ACM Transactions on Algorithms (TALG), 14(1):7, 2018. Google Scholar
  18. Junjie Luo, Hendrik Molter, and Ondřej Suchý. A Parameterized Complexity View on Collapsing k-Cores. CoRR, 2018. URL: http://arxiv.org/abs/1805.12453.
  19. Fragkiskos D. Malliaros and Michalis Vazirgiannis. To stay or not to stay: modeling engagement dynamics in social graphs. In Proceedings of the 22nd ACM International Conference on Information &Knowledge Management (CIKM '13), pages 469-478. ACM, 2013. Google Scholar
  20. Luke Mathieson. The parameterized complexity of editing graphs for bounded degeneracy. Theoretical Computer Science, 411(34-36):3181-3187, 2010. Google Scholar
  21. Stephen B. Seidman. Network structure and minimum degree. Social Networks, 5(3):269-287, 1983. Google Scholar
  22. Shuichi Ueno, Yoji Kajitani, and Shin'ya Gotoh. On the nonseparating independent set problem and feedback set problem for graphs with no vertex degree exceeding three. Discrete Mathematics, 72(1-3):355-360, 1988. Google Scholar
  23. Xin Wang, Roger Donaldson, Christopher Nell, Peter Gorniak, Martin Ester, and Jiajun Bu. Recommending Groups to Users Using User-Group Engagement and Time-Dependent Matrix Factorization. In Proceedins of the 30th AAAI Conference on Artificial Intelligence (AAAI '16), pages 1331-1337. AAAI Press, 2016. Google Scholar
  24. Shaomei Wu, Atish Das Sarma, Alex Fabrikant, Silvio Lattanzi, and Andrew Tomkins. Arrival and departure dynamics in social networks. In Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM '13), pages 233-242. ACM, 2013. Google Scholar
  25. Fan Zhang, Ying Zhang, Lu Qin, Wenjie Zhang, and Xuemin Lin. Finding Critical Users for Social Network Engagement: The Collapsed k-Core Problem. In Proceedins of the 31st AAAI Conference on Artificial Intelligence (AAAI '17), pages 245-251. AAAI Press, 2017. Google Scholar
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