Abstract
Several algorithms, namely CubeMiner, Trias, and Data-Peeler, have been recently proposed to mine closed patterns in ternary relations. We consider here the specific context where a ternary relation denotes the value of a graph adjacency matrix at different timestamps. Then, we discuss the constraint-based extraction of patterns in such dynamic graphs. We formalize the concept of δ-contiguous closed 3-clique and we discuss the availability of a complete algorithm for mining them. It is based on a specialization of the enumeration strategy implemented in Data-Peeler. Indeed, clique relevancy can be specified by means of a conjunction of constraints which can be efficiently exploited. The added-value of our strategy is assessed on a real dataset about a public bicycle renting system. The raw data encode the relationships between the renting stations during one year. The extracted δ-contiguous closed 3-cliques are shown to be consistent with our domain knowledge on the considered city.
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Cerf, L., Nguyen, T.B.N., Boulicaut, JF. (2009). Discovering Relevant Cross-Graph Cliques in Dynamic Networks. In: Rauch, J., Raś, Z.W., Berka, P., Elomaa, T. (eds) Foundations of Intelligent Systems. ISMIS 2009. Lecture Notes in Computer Science(), vol 5722. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04125-9_54
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DOI: https://doi.org/10.1007/978-3-642-04125-9_54
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