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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 are 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 

Please find our first prototype of the HyGraph package that allows for combined analysis : HyGraph-package

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