Anne LAURENT Anne LAURENT's Scientific Collaborations


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EXPEDO STIC-Asia Project

This project aims at analysing huge volumes of historical data. Existing methods are not appropriate as they are mostly based on reporting (no data mining to automatically mine relevant patterns), and no user-friendly query-based navigation exists. The targets of EXPEDO are:
  •  to consider data mining techniques,
  •  to build a prototype,
  •  to consider real data sets (e.g. agricultural data).
Partners: Cergy-Pontoise (ETIS), Tours (LI), Paris-Sud (LRI), Malaysia HELP University College (HELP UC), Indonesia Institut Teknologi Bandung (ITB), Stikom Bali, Pakistan Pakistan Science Foundation (PSF)

MIDAS - ANR Masses de données

The MIDAS project is a ‘Recherche Fondamentale’ developing and demonstrating new methods the following scientific challenges related to the construction of summaries:
• Summaries are built from infinite streams size;
• The construction of summaries must be incremental (done ‘on the fly’);
• The amount of CPU used to process compatible with the arrival rate of the elements;
• The summaries must cover the whole past part of the history of a stream.

Partners: EDF R&D, FT R&D, ENST, INRIA-Axis, LGI2P, CEREGMIA

LIP6-UPMC

B. Bouchon-Meunier, MJ Lesot, M. Rifqi (Département DAPA - Equipe MALIRE)

LIG-UJF

A. Termier

LIRMM