Publikation: DAGMA: Mining Directed Acyclic Graphs
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We present how to efficiently mine a set of directed acyclic graphs (DAGs) for unconnected, both multi- or single-rooted, and induced fragments. With a new canonical form that is based on the nodes' topological levels, our miner is faster and uses less storage than general purpose gSpan (Yan, X. and Han, J., 2002). Moreover, it can base support resp. frequency either on the number of embeddings of a fragment in the database or on the number of graphs a fragment appears in. This is crucial for finding frequent fragments in data flow graphs generated from assembly code. Extracting them into new procedures reduces the total code size. The paper shows that our miner outperforms general purpose mining and demonstrates the quantitative effects of DAG mining in program size reduction.
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WERTH, Tobias, Alexander DREWEKE, Marc WÖRLEIN, Ingrid FISCHER, Michael PHILIPPSEN, 2008. DAGMA: Mining Directed Acyclic Graphs. IADIS European Conference on Data Mining. Amsterdam, The Netherlands, 24. Juli 2008 - 26. Juli 2008. In: IADIS European Conference on Data Mining 2008, Amsterdam, The Netherlands, 24. - 26. July 2008. IADIS Press, 2008. IADIS Press, 2008, pp. 11-18BibTex
@inproceedings{Werth2008DAGMA-5793, year={2008}, title={DAGMA: Mining Directed Acyclic Graphs}, publisher={IADIS Press}, booktitle={IADIS European Conference on Data Mining 2008, Amsterdam, The Netherlands, 24. - 26. July 2008. IADIS Press, 2008}, pages={11--18}, author={Werth, Tobias and Dreweke, Alexander and Wörlein, Marc and Fischer, Ingrid and Philippsen, Michael} }
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