Density-based data partitioning strategy to approximate large-scale subgraph mining

Author:

Aridhi Sabeur,d'Orazio Laurent,Maddouri Mondher,Mephu Nguifo Engelbert

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference25 articles.

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3. S. Nijssen, J.N. Kok, A quickstart in frequent structure mining can make a difference, in: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '04, ACM, New York, NY, USA, 2004, pp. 647–652.

4. X. Yan, J. Han, gSpan: graph-based substructure pattern mining, in: Proceedings of the 2002 IEEE International Conference on Data Mining, ICDM '02, IEEE Computer Society, Washington, DC, USA, 2002, pp. 721–724.

5. M. Wörlein, T. Meinl, I. Fischer, M. Philippsen, A quantitative comparison of the subgraph miners mofa, gspan, ffsm, and gaston, in: Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'05, Springer-Verlag, Berlin, Heidelberg, 2005, pp. 392–403.

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