Full Perfect Extension Pruning for Frequent Subgraph Mining

Borgelt, Christian; Meinl, Thorsten

Full Perfect Extension Pruning for Frequent Subgraph Mining

Dateien

bookchapter.pdfGröße: 250.71 KBDownloads: 221

Datum

2009

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Sammelband

Publikationsstatus

Published

Erschienen in

ZIGHED, Djamel A., ed. and others. Mining Complex Data. Berlin: Springer, 2009, pp. 189-205. Studies in Computational Intelligence. Vol. 165

Zusammenfassung

Mining graph databases for frequent subgraphs has recently developed into an area of intensive research. Its main goals are to reduce the execution time of the existing basic algorithms and to enhance their capability to find meaningful graph fragments. Here we present a method to achieve the former, namely an improvement of what we called "perfect extension pruning'' in an earlier paper. With this method the number of generated fragments and visited search tree nodes can be reduced, often considerably, thus accelerating the search. We describe the method in detail and present experimental results that demonstrate its usefulness.

Fachgebiet (DDC)

004 Informatik

Schlagwörter

subgraph, mining, frequent

Zitieren

ISO 690

BORGELT, Christian, Thorsten MEINL, 2009. Full Perfect Extension Pruning for Frequent Subgraph Mining. In: ZIGHED, Djamel A., ed. and others. Mining Complex Data. Berlin: Springer, 2009, pp. 189-205. Studies in Computational Intelligence. Vol. 165

BibTex

@incollection{Borgelt2009Perfe-5878,
  year={2009},
  title={Full Perfect Extension Pruning for Frequent Subgraph Mining},
  number={Vol. 165},
  publisher={Springer},
  address={Berlin},
  series={Studies in Computational Intelligence},
  booktitle={Mining Complex Data},
  pages={189--205},
  editor={Zighed, Djamel A.},
  author={Borgelt, Christian and Meinl, Thorsten}
}

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Universitätsbibliographie

Ja