PDSC: Clustering Object Paths from RFID Data Sets
Huifang Deng, Guosheng Lin · 2009
Radio Frequency Identification (RFID) is playing a more and more important role in our life. How to analyze and discover knowledge from RFID data sets is an urgent and challenging research field. Each tracking object will form a path when it moves through different locations. We present a novel algorithm called PDSC (Path Division and Segments Clustering) to cluster such path data. Considering that there may be some common segments among paths although the full paths are not so similar in general and the common segments may reveal some interesting patterns, we focus on segments clustering in this paper. Firstly we develop an algorithm to divide paths into segments. Secondly a novel similarity definition and algorithm are proposed to measure the similarity of two path segments. Finally we develop a robust clustering algorithm to discover segment clusters. An experimental system is developed to visualize data in every phase. Experimental results demonstrate that PDSC correctly discovers the common path segments.