In many real-life businesses, the service provider/seller keeps a log of the visitors’ behavior as a way to assess the efficiency of the current business/operation model and find room for improvement. For example, by tracking when visitors entering attractions in a theme park, theme park owners can detect when and where congestion may occur, thus having contingency plans to reroute the visitors accordingly. Similarly, a Cable TV service provider can track channel switching events at each household to identify uninteresting channels. Subsequently, the repertoire of channels up for subscription can evolve over time to better serve the entertainment demand of subscribers. All tracking activities can be done anonymously so as to protect the customers’ privacy. Given a large amount of data about customer behavior, we would like to succinctly represent it so that insights can be inferred more quickly and conveniently.