Data set features of cloud sensor system

Data set features of cloud sensor system

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In this era of exponential growth in the scale of data, information overload has become an urgent problem, and the use of increasingly flexible sensor cloud systems (SCS) for data collection has become a mainstream trend. Recommendation algorithms can search massive data sets to uncover information that meets the needs of users based on their inter...

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... Generally, user preferences can be roughly divided into long-term and short-term [32]. Long-term preferences often refer to the interests of users. ...
... To fully exploit the potential of A-DNR, we explore the impact of the depth of hidden layers in the feature interaction layer on model performance. In this experiment, the size of the hidden layer is set to [8], [16,8], [32,16,8], [64,32,16,8], [128,64,32,16,8], and other parameters remain unchanged. The experimental results are shown in Table 11. ...
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... Many experiments have shown that deep neural networks (DNNs) are used in several fields because of their ability to capture complex and deeper information, including image segmentation [1], natural language processing [2,3], speech recognition [4], and recommendation systems [5][6][7]. Dailing Zhang et al. [8] designed deep learning-based frameworks that consist of both convolutional and recurrent neural networks to precisely identify human intentions in brain-computer interfaces. Kaixuan Chen et al. [9] proposed a semisupervised deep model for imbalanced activity recognition and pattern-balanced cotraining for extracting and preserving the latent activity patterns to improve the robustness of co-training on imbalanced data. ...
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