Link Prediction Based on Graph Neural Networks

link Prediction Based on Graph Neural NetworksMuhan ZhangDepartment of CSEW ashington University in St. ChenDepartment of CSEW ashington University in St. Prediction is a key problem for network -structured data. link predictionheuristics use some score functions, such as common neighbors and Katz index,to measure the likelihood of links. They have obtained wide practical uses due totheir simplicity, interpretability, and for some of them, scalability. However, everyheuristic has a strong assumption on when two nodes are likely to link , whichlimits their effectiveness on Networks where these assumptions fail.

However, it is shown that high-order heuristics such as rooted PageRank and Katz often have much better performance than first and second-order ones [6]. To effectively learn good high-order features, it seems that we need a very large hop number h so that the enclosing subgraph becomes the entire network.

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  Based, Network, Link, Prediction, Graph, Neural, Pagerank, Link prediction based on graph neural networks

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