Hybrid fragment mining with MoFA and FSG

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MEINL, Thorsten, Michael R. BERTHOLD, 2004. Hybrid fragment mining with MoFA and FSG. 2004 IEEE International Conference on Systems, Man and Cybernetics. The Hague, Netherlands. In: 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583). 2004 IEEE International Conference on Systems, Man and Cybernetics. The Hague, Netherlands. IEEE, pp. 4559-4564. ISBN 0-7803-8567-5

@inproceedings{Meinl2004Hybri-5541, title={Hybrid fragment mining with MoFA and FSG}, year={2004}, doi={10.1109/ICSMC.2004.1401250}, isbn={0-7803-8567-5}, publisher={IEEE}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)}, pages={4559--4564}, author={Meinl, Thorsten and Berthold, Michael R.} }

Berthold, Michael R. Berthold, Michael R. First publ. in: 2004 IEEE International Conference on Systems, Man & Cybernetics, The Hague, Netherlands, 10 - 13 October 2004. Piscataway, NJ : IEEE Operations Center, 2004, pp. 4559-4564 2011-03-24T15:56:18Z 2011-03-24T15:56:18Z Meinl, Thorsten application/pdf In the last few years a number of different subgraph mining algorithms have been proposed. They are often used for finding frequent fragments in molecular databases. All these algorithms behave quite well when used on small datasets of not more than a few thousand molecules. However, they all fail on larger amounts of data because they are either time consuming or have enormous memory requirements. In this paper we present a hybrid mining technique that overcomes the individual problems of the underlying algorithms and outperforms the individual methods impressively on large databases. 2004 deposit-license Meinl, Thorsten Hybrid fragment mining with MoFA and FSG eng

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