@InProceedings{woerlein05quantitative,
  author    = {W\"orlein, Marc and Meinl, Thorsten and Fischer, Ingrid and Philippsen, Michael},
  title     = {A quantitative comparison of the subgraph miners {MoFa}, {gSpan}, {FFSM}, and {Gaston}},
  booktitle = {Proc. of Principles and Practice of Knowledge Discovery in Databases (PKDD 2005)},
  year      = {2005},
  volume    = {3721},
  series    = lncs,
  pages     = {392--403},
  publisher = Springer,
  abstract  = {Several new miners for frequent subgraphs have been published recently. Whereas new approaches are presented in detail, the quantitative evaluations are often of limited value: only the performance on a small set of graph databases is discussed and the new algorithm is often only compared to a single competitor based on an executable. It remains unclear, how the algorithms work on bigger/other graph databases and which of their distinctive features is best suited for which database. We have re-implemented the subgraph miners MoFa, gSpan, FFSM, and Gaston within a common code base and with the same level of programming expertise and optimization effort. This paper presents the results of a comparative benchmarking that ran the algorithms on a comprehensive set of graph databases.},
  doi       = {10.1007/11564126_39},
  isbn      = {3-540-29244-6, 978-3-540-29244-9},
  keywords  = {chemoinformatics; subgraph isomorphism; data mining; subgraph mining},
  location  = {Porto, Portugal},
  owner     = {Sebastian},
  timestamp = {2012.06.07},
}

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