Short description : A research project funded by ANR and DFG, combines a dynamic property graph model with time-series and graph streams.
Graphs are simple yet highly expressive data structures for modeling and analyzing relationships between real-world objects. As the structure and content of graphs is continuously changing, e.g. in social networks or transport and mobility networks, novel data models and analysis mechanisms are needed. Our goal is to develop HyGraph, a new hybrid data model that seamlessly combines temporal graphs with time-series and enables high-frequency updates through graph streams. This combination in a unified hybrid model paves the way to novel unprecedented query, analysis, data mining and machine learning tasks.
Please check our website for more information : Hygraph
LIRIS UMR 5205 - IMAGE AND INFORMATION SYSTEMS COMPUTING LABORATORY - University of Lyon, France
Funding / Cooperation
DFG : from the german side
ANR : from the french side