Analyzing The Trajectories Of Customers By Using LCSS Approach

摘要

To understand the customer behavior, we need to analyze the movements of customers inside the mall, because it helps to organize the aisles and shelves according to the customer’s needs. There are a lot of approaches of clustering data, but the most useful for paths is the longest common subsequence LCSS; it is an efficient method that groups similar trajectories in the same cluster. In this paper, we detect the localizations of customers by using Bluetooth Low Energy Beacons, and we generate the trajectories. Then, we use Longest Common Subsequence method to group the trajectories in order to find hot areas and extract major trajectories of the customers.