AISep 25, 2020
Process mining classification with a weightless neural network
arXiv:2009.12416v13 citations
Originality Synthesis-oriented
AI Analysis
This work addresses classification challenges in process mining for business analysts, but it appears incremental as it applies an existing neural network method to a specific domain.
The paper tackled the problem of classifying business process flows in process mining by proposing a weightless neural network (WiSARD) with a graph-to-retina codification, achieving improved classification performance with small training sets.
Using a weightless neural network architecture WiSARD we propose a straightforward graph to retina codification to represent business process graph flows avoiding kernels, and we present how WiSARD outperforms the classification performance with small training sets in the process mining context.