Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : ETIS – ENSEA / Université de Cergy-Pontoise / CNRS
Durée : 6 mois
Contact : claudia.marinica@u-cergy.fr
Date limite de publication : 2016-04-30
Contexte :
Object: Internship Master / Engineer
Place: Paris Area, ETIS Lab, Université de Cergy-Pontoise, Cergy-Pontoise, France (http://www-etis.ensea.fr/)
Subject: Privacy in mining of semantic trajectories among moving objects
Period: 6 months internship from April/May to September/October 2015 – approx. 508€/month
Supervision:
– Dimitris Kotzinos, PU, UCP, Dimitrios.Kotzinos@u-cergy.fr
– Claudia Marinica, MCF, UCP, Claudia.Marinica@u-cergy.fr
Applications (with CV and motivation letter) should be sent to Claudia.Marinica@u-cergy.fr .
Sujet :
Description: Trajectory pattern mining proposes to extract from location-like data frequent movement/mobility behaviour that characterise the individuals. Significant advances have been made with regard to knowledge discovery starting with the pioneer work of Giannotti et al. in 2009 [2], so lately the main interest in this research area went from efficient trajectory pattern mining to the possible risks that the discovered movement behaviour can bring to individual privacy (e.g. GeoKDD project [1]).
On the other side, the semantic web is a research area aiming to provide an easy way to find, share, reuse, etc information. To this end, it proposed a set of languages for knowledge representation, but also defines important notion such as “ontologies” permitting to represent domain semantics.
First works combining semantic web and trajectory analysis propose either to use ontologies in order to understand user’s behaviour [3] or to use taxonomies in order to improve user’s privacy [4]. Moreover, we would like to assess the threats that the addition of semantics will bring to the users’ privacy through the provision of more detailed information for the movements.
The goal of this internship is:
(1) first to study the existing methods combining semantic web and trajectory analysis in order to (mainly) improve user’s privacy;
(2) second to propose a new approach for using semantic information on available trajectories so as to improve the overall understanding of the trajectories themselves, while offering enhanced privacy considerations.
Applications (with CV and motivation letter) should be sent to Claudia.Marinica@u-cergy.fr .
[1] Mirco Nanni, Roberto Trasarti, Chiara Renso, Fosca Giannotti, and Dino Pedreschi (2010) Advanced knowledge discovery on movement data with the GeoPKDD system. EDBT, ACM International Conference Proceeding Series, page 693-696. ACM.
[2] Fosca Giannotti, Mirco Nanni, Fabio Pinelli, and Dino Pedreschi. 2007. Trajectory pattern mining. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD ’07). ACM, New York, NY, USA, 330-339.
[2] C. Renso, M. Baglioni, J. A. F. de Macˆedo, R. Trasarti, and M. Wachowicz. How you move reveals who you are: understanding human behavior by analyzing trajectory data. Knowl. Inf. Syst., 37(2):331–362, 2013.
[2] Anna Monreale, Roberto Trasarti, Chiara Renso, Dino Pedreschi, and Vania Bogorny. 2010. Preserving privacy in semantic-rich trajectories of human mobility. 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS. 47-54.
Profil du candidat :
Knowledge in data mining techniques and programming skills are required.
Formation et compétences requises :
Knowledge in data mining techniques and programming skills are required.
Adresse d’emploi :
Laboratoire ETIS, UCP, 2 Avenue Adolphe Chauvin, 95300, Cergy-Pontoise