To extend the proposed RCW generation algorithm to handle dynamic graphs where the graph structure changes over time, we can introduce a mechanism to update the RCWs as the graph evolves. This can be achieved by implementing a continuous monitoring system that tracks changes in the graph structure and triggers the algorithm to recompute the RCWs accordingly.
One approach could be to set up a real-time data pipeline that captures the graph updates and feeds them into the RCW generation algorithm. Whenever a change is detected in the graph, the algorithm can be invoked to adapt the RCWs to reflect the new graph configuration. This adaptive process ensures that the explanations provided by the RCWs remain relevant and accurate in the context of dynamic graph changes.
Additionally, incorporating techniques from online learning and incremental algorithms can help in efficiently updating the RCWs without having to recompute everything from scratch. By incrementally updating the RCWs based on the incremental changes in the graph, the algorithm can keep up with the dynamic nature of the graph data and provide timely and up-to-date explanations.