Advanced Pruning Strategies to Speed Up Mining Closed Molecular Fragments
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2004
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2004 IEEE International Conference on Systems, Man & Cybernetics, The Hague, Netherlands, 10 - 13 October 2004. IEEE Operations Center, 2004, pp. 4565-4570
Zusammenfassung
In recent years several algorithms for mining frequent subgraphs in graph databases have been proposed, with a major application area being the discovery of frequent substructures of biomolecules. Unfortunately, most of these algorithms still struggle with fairly long execution times if larger substructures or molecular fragments are desired. In this paper we describe two advanced pruning strategies equivalent sibling pruning and perfect extension pruning that can be used to speed up the MoFa algorithm (introduced in [2]) in the search for closed molecular fragments, as we demonstrate with experiments on the NCI s HIV database.
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molecular fragment, closed fragment, graph mining, pruning, perfect extension
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BORGELT, Christian, Thorsten MEINL, Michael R. BERTHOLD, 2004. Advanced Pruning Strategies to Speed Up Mining Closed Molecular Fragments. In: 2004 IEEE International Conference on Systems, Man & Cybernetics, The Hague, Netherlands, 10 - 13 October 2004. IEEE Operations Center, 2004, pp. 4565-4570BibTex
@inproceedings{Borgelt2004Advan-5431, year={2004}, title={Advanced Pruning Strategies to Speed Up Mining Closed Molecular Fragments}, publisher={IEEE Operations Center}, booktitle={2004 IEEE International Conference on Systems, Man & Cybernetics, The Hague, Netherlands, 10 - 13 October 2004}, pages={4565--4570}, author={Borgelt, Christian and Meinl, Thorsten and Berthold, Michael R.} }
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