Detecting trends in social bookmarking systems using a probabilistic generative model and smoothing


We propose a method for the detection of trends in social bookmarking systems. Compared to other work in this emerging field, our approach has a more sound statistical basis. In order to cope with the problem of vanishing probabilities due to data sparsity, we apply smoothing and show that it allows for an easy calibration of our trend detector resulting in… (More)
DOI: 10.1109/ICPR.2008.4761260


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