Eliminating Rare Event Patterns from Business Process Event Streams

This paper discusses the problem of detecting and removing infrequent behavior from event streams of business processes. We propose an algorithm based on pattern mining to identify rare event patterns and eliminate them from the stream. Our approach is able to reduce noise and improve the accuracy of process analysis. We evaluate our method on a real-world dataset and show its effectiveness in detecting and removing rare event patterns.