Tools and prototypes developed within the research projects and PhD theses under my supervision:

  • COBPAM - the algorithm we proposed for discovering behavioral patterns is available as a plugin (BehavioralPatternMining package) in the Prom framework (https://promtools.org) (software that integrates research contributions in the field of process mining). It also integrates contextual analysis of patterns and their visualization.
  • PPM-OC (Object centric predictive process monitoring) is software that enables predictive monitoring of process execution based on its execution history. We use an LSTM-type deep learning architecture that we adapt and extend to take into account the presence and intersection of multiple objects. Link: https://github.com/wissamgherissi/ PPM-OC
  • A framework for predictive monitoring (PPM) that allows the integration of different predictive models and graph embeddings. Link: https://github.com/wissam-gherissi
  • EmailMining: a prototype that uses machine learning to i) extract activities from emails and ii) build business process instances, which group together these activities involved in achieving a common goal. The approach is applied to an open data corpus. Link:
    https://github.com/Raphaaal_icpm_emails_process_mining\