APM

Learning of Process Representations Using Recurrent Neural Networks

Setup

Use Miniconda for the easiest way to setup an environment.

Using Miniconda

1. Install Miniconda (make sure to use a Python 3 version)
2. After setting up miniconda you can make use of the conda command in your command line (Powershell, CMD, Bash)
3. We suggest that you set up a dedicated environment for this project by running conda env create -f environment.yml
   • This will setup a virtual conda environment with all necessary dependencies.
   • If your device does have a GPU replace tensorflow with tensorflow-gpu in the environement.yml
4. Depending on your operating system you can activate the virtual environment with conda activate replearn on Linux and macOS, and activate ad on Windows (cmd only).
5. If you want to make use of a GPU, you must install the CUDA Toolkit. To install the CUDA Toolkit on your computer refer to the TensorFlow installation guide.
6. If you want to quickly install the replearn package, run pip install -e . inside the root directory.
7. Now you can start the notebook server by jupyter notebook notebooks.

Jupyter Notebooks

Check the notebooks directory for example Jupyter Notebooks.

Datasets

• Synthetic event logs for multi-perspective trace clustering
• Extended synthetic event logs for multi-perspective trace clustering