Using Event Log Timing Information to Assist Process Scenario Discoveries

Event logs contain abundant information, such as activity names, time stamps, activity executors, etc. However, much of existing trace clustering research has been focused on applying activity names to assist process scenarios discovery. In addition, many existing trace clustering algorithms commonly used in the literature, such as k-means clustering approach, require prior knowledge about the number of process scenarios existed in the log, which sometimes are not known aprior.