Full Perfect Extension Pruning for Frequent Graph Mining

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2006
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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06). - IEEE, 2006. - pp. 263-268. - ISBN 0-7695-2702-7
Abstract
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 [2]. With it the number of generated fragments and visited search tree nodes can be reduced, thus accelerating the search.
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004 Computer Science
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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), Dec 18, 2006 - Dec 22, 2006, Hong Kong, China
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Cite This
ISO 690BORGELT, Christian, Thorsten MEINL, 2006. Full Perfect Extension Pruning for Frequent Graph Mining. Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06). Hong Kong, China, Dec 18, 2006 - Dec 22, 2006. In: Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06). IEEE, pp. 263-268. ISBN 0-7695-2702-7. Available under: doi: 10.1109/ICDMW.2006.82
BibTex
@inproceedings{Borgelt2006-12Perfe-5487,
  year={2006},
  doi={10.1109/ICDMW.2006.82},
  title={Full Perfect Extension Pruning for Frequent Graph Mining},
  isbn={0-7695-2702-7},
  publisher={IEEE},
  booktitle={Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)},
  pages={263--268},
  author={Borgelt, Christian and Meinl, Thorsten}
}
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