ParkAnalyzer: Characterizing the movement patterns of visitors VAST 2015 Mini-Challenge 1

The 2015 VAST challenge features movement tracking (Mini- Challenge 1 (MC1)) and communication information (Mini- Challenge 2 (MC2)) datasets of all visitors in an amusement park over a three-day weekend. The data includes around 25 million individual movement records, along with 4 million communication records. Analyzing and exploring such large-scale datasets require intelligent data mining methods that characterize the overall trends and anomalies, as well as interactive visual interfaces to support investigation at different spatiotemporal granularities. The objective of MC1 was to characterize the behavior of different groups of visitors, compare different activity patterns over the three days, and discover anomalies or unusual behavior patterns that relate to the crime that occurred during the weekend. We utilized both movement data provided in MC1 and communication data provided in MC2 to answer the questions asked in MC1.