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DANCer: Dynamic Attributed Network with Community Structure Generator

Abstract : We propose a new generator for dynamic attributed networks with community structure which follow the known properties of real-world networks such as preferential attachment, small world and ho-mophily. After the generation, the different graphs forming the dynamic network as well as its evolution can be displayed in the interface. Several measures are also computed to evaluate the properties verified by each graph. Finally, the generated dynamic network, the parameters and the measures can be saved as a collection of files.
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Contributor : Baptiste Jeudy Connect in order to contact the contributor
Submitted on : Thursday, October 6, 2016 - 5:32:59 PM
Last modification on : Friday, August 5, 2022 - 12:45:03 PM
Long-term archiving on: : Friday, February 3, 2017 - 7:00:21 PM


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Oualid Benyahia, Christine Largeron, Baptiste Jeudy, Osmar R Zaïane. DANCer: Dynamic Attributed Network with Community Structure Generator. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2016, Riva del Garda, Italy. pp.41 - 44, ⟨10.1007/978-3-319-46131-1_9⟩. ⟨hal-01377321⟩



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