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Conference papers

Mining Disjunctive Rules in Dynamic Graphs

Thi Kim Ngan Nguyen 1 Marc Plantevit 1 Jean-François Boulicaut 1
1 DM2L - Data Mining and Machine Learning
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Recently, a generalization of association rules that hold in n-ary Boolean tensors has been proposed. Moreover, preliminary results concerning their application to dynamic relational graph analysis have been obtained. We build upon such a formalization to design more expressive local patterns in this special case of dynamic graph where the set of vertices remains unchanged though edges that connect them may appear or disappear at the different timestamps. To design the pattern domain of the so-called disjunctive rules, we have to design (a) the pattern language, (b) interestingness measures which serve as the counterpart of the popular support and confidence measures in standard association rules, and (c) an efficient algorithm that may compute every rule that satisfies some primitive constraints like minimal frequencies or minimal confidences. The approach is tested on real datasets and we discuss the expressivity and the relevancy of some computed disjunctive rules.
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Submitted on : Wednesday, August 10, 2016 - 4:16:13 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:09 PM

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Thi Kim Ngan Nguyen, Marc Plantevit, Jean-François Boulicaut. Mining Disjunctive Rules in Dynamic Graphs. 2012 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), Feb 2012, Ho Chi Minh, Vietnam. pp.74-79, ⟨10.1109/rivf.2012.6169829⟩. ⟨hal-01352944⟩



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