Welcome to the Collaboration Pattern Detection Framework documentation!
=======================================================================

.. note::
   This project and documentation is under active development.


This Python3-based framework conducts *Collaboration Pattern Detection* using methods from *Process Mining*, *Frequent Subgraph Mining* & *Graph Set Clustering* techniques.
Resulting (process) graph sets / patterns are stored in a `Graph Collection <graphCollection.html>`__ and can be exported as a file, or uploaded/downloaded from or to a Neo4j graph database.

This framework is used in the **Social Process Mining** project to detect **Collaboration Pattern** inside **Enterprise Collaboration Systems (ECS)**.


Overview
--------
1. `Preprocessing <preprocessing.html>`__: This package provides an API for preprocessing the event logs and prepare them for the collaboration pattern detection discovery algorithm.
2. `Process Mining <processMining.html>`__: This package provides an API for mining graphs (process discovery) from event logs using Process Mining discovery algorithms.
3. `Frequent Subgraph Mining <fsm.html>`__: The generated graphs are used as input for *Frequent Subgraph Mining*.
4. `Clustering Graph Sets <clustering.html>`__: The resulting sub-graphs can be clustered using graph set clustering.

----

.. toctree::
   :maxdepth: 2
   :caption: Contents:

   install
   graphCollection
   preprocessing
   processMining
   fsm
   clustering
   api