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In this work, we address a novel problem about tag co-occurrence relationship prediction across heterogeneous networks. Although tag co-occurrence has recently become a hot research topic, many studies mainly focus on how to produce the personalized recommendation leveraging the tag co-occurrence relationship and most of them are considered in a homogeneous network. So far, few studies pay attention...
The power law distribution of social tag frequency is one of the most important statistic characteristics in social tagging system. Researchers have proposed several models to predict this distribution, but these models depend on specific system. What's more, data fitting methods were failed to describe the raw data precisely compared with a mathematical model. Random Group Formation (RGF) model is...
According to the characteristic of monitoring data in geotechnical engineering, three nonlinear time series prediction models: whole-region methods (linear function, exponential function, Gauss function and Fourier function), local-region methods (linear function, power function and exponential function) and chaos neural network based on the local-region method are built up by introducing the theory...
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