A FAST ALGORITHM FOR MINING GRAPHS OF PRESCRIBED CONNECTIVITY

Natalia Vanetik

Abstract

Many real-life data sets, such as social and biological networks and biochemical data, are naturally and easily modeled as large labeled graphs. Finding patterns of interest in these graphs is an important task, due to the nature of the data not all of the patterns need to be taken into account. Intuitively, if a pattern has high connectivity, it implies that there is a strong connection between data items. In this paper, we present a novel algorithm for finding frequent graph patterns with prescribed connectivity in large single-graph data sets. We employ the Dinitz-Karzanov-Lomonosov cactus minimum cut structure of a graph to perform the task efficiently. We also prove that the suggested algorithm generates no more candidate graphs than any other algorithm whose graph extension procedure we use at the first step.

References

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Paper Citation


in Harvard Style

Vanetik N. (2011). A FAST ALGORITHM FOR MINING GRAPHS OF PRESCRIBED CONNECTIVITY . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 5-13. DOI: 10.5220/0003628300050013


in Bibtex Style

@conference{kdir11,
author={Natalia Vanetik},
title={A FAST ALGORITHM FOR MINING GRAPHS OF PRESCRIBED CONNECTIVITY},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={5-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003628300050013},
isbn={978-989-8425-79-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - A FAST ALGORITHM FOR MINING GRAPHS OF PRESCRIBED CONNECTIVITY
SN - 978-989-8425-79-9
AU - Vanetik N.
PY - 2011
SP - 5
EP - 13
DO - 10.5220/0003628300050013