A New Density Clustering Method of Uncertain RFID Data Mining

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Provided by: AICIT
Topic: Big Data
Format: PDF
With the adoption of the mobile devices with location sensing and positioning functions, such as GPS and RFID, people now are able to acquire present locations and other information. As the availability of trajectory data prospers, mining activities hidden in raw trajectories becomes a hot research problem. In this paper, the spatial, temporal and the probability relationships among data points of trajectories are considered to extract the stop location of ROI that refer to regions in where users are likely to have some kinds of activities. In order to extract such locations, an Uncertain Sequential RFID event Density Clustering algorithm (USRDC) is proposed to mining clusters.
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