论文标题
Wiki-CS：基于Wikipedia的基于图形神经网络的基准
Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks
论文作者
论文摘要
我们提出了Wiki-CS，这是一种来自Wikipedia的新型数据集，用于基准图形神经网络。数据集由与计算机科学文章相对应的节点组成，其边缘基于超链接和10个类，代表该领域的不同分支。我们使用数据集评估半监督节点分类和单连接链接预测模型。我们的实验表明，这些方法在新域上的表现良好，结构特性与早期基准不同。该数据集在https://github.com/pmernyei/wiki-cs-dataset上公开可用，以及数据管道和基准实验的实现。
We present Wiki-CS, a novel dataset derived from Wikipedia for benchmarking Graph Neural Networks. The dataset consists of nodes corresponding to Computer Science articles, with edges based on hyperlinks and 10 classes representing different branches of the field. We use the dataset to evaluate semi-supervised node classification and single-relation link prediction models. Our experiments show that these methods perform well on a new domain, with structural properties different from earlier benchmarks. The dataset is publicly available, along with the implementation of the data pipeline and the benchmark experiments, at https://github.com/pmernyei/wiki-cs-dataset .
