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Temporal Subgraph Isomorphism
Author(s)
Date Issued
2013-08-28
Date Available
2016-04-06T11:14:28Z
Abstract
Temporal information is increasingly available with network data sets. This information can expose underlying processes in the data via sequences of link activations. Examples range from the propagation of ideas through a scientific collaboration network, to the spread of disease via contacts between infected and susceptible individuals. We focus on the flow of funds through an online financial transaction network, in which given patterns might signify suspicious behaviour. The search for these patterns may be formulated as a temporally constrained subgraph isomorphism problem. We compare two algorithms which use temporal data at different stages during the search, and empirically demonstrate one to be significantly more efficient.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2013 ACM
Language
English
Status of Item
Peer reviewed
Part of
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Conference Details
2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Ontario, Canada, 25-28 August 2013
This item is made available under a Creative Commons License
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