Our objective is to build and develop models and tools to index, manipulate, analyze, and recommend multi-modal data from heterogeneous sources in a personalized way. We seek to represent and exploit the content of potentially massive and heterogeneous data jointly with the knowledge related to the field.
Our main applications deal with:
- Multi-modal linguistic data
- Web intelligence data
- Data from sensor networks (Defense and Environment)
- Sentiment and emotions analysis for automatic recommendation of content based on text and data mining approaches (in collaboration with R2I team at LIS lab).
We are also working on data security and privacy by proposing models to define appropriate access control policies. More specifically, we are working on the security of publication/subscription networks with applications using the mqtt protocol, which is one of the standards of the Internet of Things. This work is carried out in collaboration with the GePaSud laboratory of the University of French Polynesia. Applications in the field of environmental monitoring are planned.