Fischer I, Meinl T (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: 4578-4582
Conference Proceedings Title: Proceedings of the 2004 IEEE International Converence on Systems, Man and Cybernetics
Event location: Den Haag, The Netherlands
ISBN: 0-7803-8567-5
URI: http://www2.informatik.uni-erlangen.de/publication/download/graphBasedDM_SMC2004.pdf
DOI: 10.1109/ICSMC.2004.1401253
In the last years quite a lot of algorithms concerning frequent graph pattern mining have been published. In this paper an overview on the different methods for graph data mining is given, starting with the greedy searches proposed in the middle of the ninties. The ILP-based approaches are taken into account as well as ideas influenced by basket analyses proposed lately. A remaining question is how the different approaches can be tailored to meet the needs for mining molecules. In this area special problems occur as molecules are not just "normal arbitrary graphs". There are structures that are typical and frequent as rings and chains, some node types resp. atoms occur more often than others. It is an unsolved question how chemically isomorphic mining can be handled. © 2004 IEEE.
APA:
Fischer, I., & Meinl, T. (2004). Graph Based Molecular Data Mining - An Overview. In Thissen, Wil ; Wieringa, Peter ; Pantic, Maja ; Ludema, Marcel (Eds.), Proceedings of the 2004 IEEE International Converence on Systems, Man and Cybernetics (pp. 4578-4582). Den Haag, The Netherlands, NL: IEEE.
MLA:
Fischer, Ingrid, and Thorsten Meinl. "Graph Based Molecular Data Mining - An Overview." 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. 4578-4582.
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