Triggering Patterns of Topology Changes in Dynamic Graphs

Abstract : To describe the dynamics taking place in networks that structurally change over time, we propose an approach to search for attributes whose value changes impact the topology of the graph. In several applications, it appears that the variations of a group of attributes are often followed by some structural changes in the graph that one may assume they generate. We formalize the triggering pattern discovery problem as a method jointly rooted in sequence mining and graph analysis. We apply our approach on three real-world dynamic graphs of different natures - a co-authoring network, an airline network, and a social bookmarking system - assessing the relevancy of the triggering pattern mining approach.
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Mehdi Kaytoue, Yoann Pitarch, Marc Plantevit, Céline Robardet. Triggering Patterns of Topology Changes in Dynamic Graphs. The 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug 2014, Beijing, China, China. pp.55:1--55:17, ⟨10.1109/ASONAM.2014.6921577⟩. ⟨hal-01301075⟩



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