12 citations · 30 across the 6 of their papers we have counts for
6 papers
A Deep Learning Approach for Repairing Missing Activity Labels in Event Logs for Process Mining
Yang Lu, Qifan Chen, Simon K. Poon
Process mining is a relatively new subject that builds a bridge between traditional process modeling and data mining. Process discovery is one of the most critical parts of process…
A Novel Approach to Discover Switch Behaviours in Process Mining
Yang Lu, Qifan Chen, Simon Poon
Process mining is a relatively new subject which builds a bridge between process modelling and data mining. An exclusive choice in a process model usually splits the process into d…
Discovering Redundant Activities in Event Logs for the Simplification of Process Models
Qifan Chen, Yang Lu, Simon Poon
Process mining acts as a valuable tool to analyse the behaviour of an organisation by offering techniques to discover, monitor and enhance real processes. The key to process mining…
A Multi-View Framework to Detect Redundant Activity Labels for More Representative Event Logs in Process Mining
Qifan Chen, Yang Lu, Charmaine S. Tam +1
Process mining aims to gain knowledge of business processes via the discovery of process models from event logs generated by information systems. The insights revealed from process…
A Robust and Accurate Approach to Detect Process Drifts from Event Streams
Yang Lu, Qifan Chen, Simon Poon
Business processes are bound to evolve as a form of adaption to changes, and such changes are referred as process drifts. Current process drift detection methods perform well on cl…
Detecting and Understanding Branching Frequency Changes in Process Models
Yang Lu, Qifan Chen, Simon Poon
Business processes are continuously evolving in order to adapt to changes due to various factors. One type of process changes are branching frequency changes, which are related to…