Hybrid Fragment Mining with MoFa and FSG

Meinl T, Berthold MR (2004)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2004

Publisher: IEEE

Edited Volumes: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Pages Range: 4559-4564

Conference Proceedings Title: Proceedings of the 2004 IEEE International Converence on Systems, Man and Cybernetics

Event location: Den Haag, The Netherlands NL

ISBN: 0-7803-8567-5

URI: http://www2.informatik.uni-erlangen.de/publication/download/hybridFragmentMining_SMC2004.pdf

DOI: 10.1109/ICSMC.2004.1401250

Abstract

In the last few years a number of different sub-graph mining algorithms have been proposed. They are often used for nding 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 IEEE.

How to cite

APA:

Meinl, T., & Berthold, M.R. (2004). Hybrid Fragment Mining with MoFa and FSG. In Thissen, Wil ; Wieringa, Peter ; Pantic, Maja ; Ludema, Marcel (Eds.), Proceedings of the 2004 IEEE International Converence on Systems, Man and Cybernetics (pp. 4559-4564). Den Haag, The Netherlands, NL: IEEE.

MLA:

Meinl, Thorsten, and Michael R. Berthold. "Hybrid Fragment Mining with MoFa and FSG." Proceedings of the 2004 IEEE International Conference on Systems, Man and Cybernetics, Den Haag, The Netherlands Ed. Thissen, Wil ; Wieringa, Peter ; Pantic, Maja ; Ludema, Marcel, IEEE, 2004. 4559-4564.

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