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Abstract

We present algorithms for finding large graph matchings in the streaming model. In this model, applicable when dealing with massive graphs, edges are streamed-in in some arbitrary order rather than residing in randomly accessible memory. For ε> 0, we achieve a \(\frac1{1+\epsilon}\) approximation for maximum cardinality matching and a \(\frac1{2+\epsilon}\) approximation to maximum weighted matching. Both algorithms use a constant number of passes and \(\tilde O(|V|)\) space.

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© 2005 Springer-Verlag Berlin Heidelberg

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McGregor, A. (2005). Finding Graph Matchings in Data Streams. In: Chekuri, C., Jansen, K., Rolim, J.D.P., Trevisan, L. (eds) Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques. APPROX RANDOM 2005 2005. Lecture Notes in Computer Science, vol 3624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538462_15

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  • DOI: https://doi.org/10.1007/11538462_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28239-6

  • Online ISBN: 978-3-540-31874-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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