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Parallel algorithms for anomalous subgraph detection
Concurrency and computation, 2017-02, Vol.29 (3), p.np-n/a
Zhao, Jieyu
Li, Jianxin
Zhou, Baojian
Chen, Feng
Tomchik, Paul
Ju, Wuyang
2017
Details
Autor(en) / Beteiligte
Zhao, Jieyu
Li, Jianxin
Zhou, Baojian
Chen, Feng
Tomchik, Paul
Ju, Wuyang
Titel
Parallel algorithms for anomalous subgraph detection
Ist Teil von
Concurrency and computation, 2017-02, Vol.29 (3), p.np-n/a
Ort / Verlag
Hoboken: Wiley Subscription Services, Inc
Erscheinungsjahr
2017
Link zum Volltext
Quelle
Wiley Online Library Journals Frontfile Complete
Beschreibungen/Notizen
Summary For the many application domains concerning entities and their connections, often their data can be formally represented as graphs and an important problem is detecting an anomalous subgraph within it. Numerous methods have been proposed to speed‐up anomalous subgraph detection; however, each incurs non‐trivial costs on detection accuracy. In this paper, we formulate the anomalous subgraph detection problem as the maximization of a non‐parametric scan statistic and then approximate it to a submodular maximization problem. We propose two parallel algorithms: non‐coordination anomalous subgraph detection (NCASD) and under‐coordination anomalous subgraph detection (UCASD)for the anomalous subgraph detection. To the best of our knowledge, this paper is the first to solve this problem in parallel. NCASD emphasizes speed at the expense of approximation guarantees, while UCASD achieves a higher approximation factor through additional coordination controls and reduced parallelism. The experiments demonstrate the effectiveness and efficiency of our proposed approaches in a real‐world application domain (water pollution detection), comparing them with five other state‐of‐the‐art methods. Copyright © 2016 John Wiley & Sons, Ltd.
Sprache
Englisch
Identifikatoren
ISSN: 1532-0626
eISSN: 1532-0634
DOI: 10.1002/cpe.3769
Titel-ID: cdi_proquest_miscellaneous_1880010865
Format
–
Schlagworte
Algorithms
,
anomalous subgraph detection
,
Approximation
,
Concurrency
,
Efficiency
,
Graphical representations
,
Graphs
,
Joints
,
Mathematical analysis
,
Maximization
,
parallel algorithm
,
Pollution detection
,
Statistics
,
submodular maximization
,
Water pollution
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