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• W2952753235 abstract "Finding a maximum-cardinality or maximum-weight matching in (edge-weighted) undirected graphs is among the most prominent problems of algorithmic graph theory. For $n$-vertex and $m$-edge graphs, the best known algorithms run in $widetilde{O}(msqrt{n})$ time. We build on recent theoretical work focusing on linear-time data reduction rules for finding maximum-cardinality matchings and complement the theoretical results by presenting and analyzing (thereby employing the kernelization methodology of parameterized complexity analysis) new (near-)linear-time data reduction rules for both the unweighted and the positive-integer-weighted case. Moreover, we experimentally demonstrate that these data reduction rules provide significant speedups of the state-of-the art implementations for computing matchings in real-world graphs: the average speedup factor is 4.7 in the unweighted case and 12.72 in the weighted case." @default.
• W2952753235 created "2019-06-27" @default.
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• W2952753235 date "2018-06-25" @default.
• W2952753235 modified "2023-10-03" @default.
• W2952753235 title "Data Reduction for Maximum Matching on Real-World Graphs: Theory and Experiments" @default.
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• W2952753235 hasPublicationYear "2018" @default.
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