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Profiling users of the Vélo 'v bike sharing system

Albrecht Zimmermann 1 Mehdi Kaytoue 1 Marc Plantevit 1 Céline Robardet 1 Jean-François Boulicaut 1 
1 DM2L - Data Mining and Machine Learning
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Detecting and characterizing geographical areas that are attractive places for specific people, in specific contexts, is an important but challenging new problem. Mobility traces and their related circumstances can be modeled thanks to an augmented graph in which nodes denote geographic locations and edges are represented by a set of transactions that describe users' demographic information (e.g. age, gender, etc.) as well as the conditions of the movement (e.g. day/night, holiday , transportation mode, etc.). We propose to extract connected subgraphs that are related to some user profiles, and use it to understand the usages of the Vélo 'v bike sharing system.
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Contributor : Marc Plantevit Connect in order to contact the contributor
Submitted on : Friday, September 4, 2015 - 10:36:37 AM
Last modification on : Friday, September 30, 2022 - 11:34:16 AM
Long-term archiving on: : Saturday, December 5, 2015 - 12:02:07 PM


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  • HAL Id : hal-01193017, version 1


Albrecht Zimmermann, Mehdi Kaytoue, Marc Plantevit, Céline Robardet, Jean-François Boulicaut. Profiling users of the Vélo 'v bike sharing system. 2nd International Workshop on Mining Urban Data (MUD), Ioannis Katakis, François Schnitzler, Thomas Liebig, Dimitrios Gunopulos, Katharina Morik,Gennady L. Andrienko, Shie Mannor, Jul 2015, Lille, France. pp.63-64. ⟨hal-01193017⟩



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