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Journal of Cloud Computing

Advances, Systems and Applications

Fig. 2 | Journal of Cloud Computing

Fig. 2

From: Recommend what to cache: a simple self-supervised graph-based recommendation framework for edge caching networks

Fig. 2

The overall framework of SimSGR. Following the scheme of CL, one view of the contrastive positive pair \(Z\) is encoded from the original graph \(G\), and the other \(Z^{\prime}\) is generated from the Mixing layer by mixing both the neighboring nodes and similar nodes. The two contrastive views are then converted into the rating matrices \(R\) and \(R^{\prime}\) in the Conversion layer, SimSGR aims to maintain the invariance of \(R\) and \(R^{\prime}\), and the covariance criterion is used to prevent the model from collapsing

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