Application of sequential pattern mining to the analysis of visitor trajectories

Abstract : In this work, we demonstrate the proof of concept of clustering 254 visitors based on their trajectories in a museum. We used a real dataset from Haifa Museum, where each trajectory is treated as a sequence of itemsets. We applied simACS as a similarity measure between any two sequences.