16 datasets found

The dataset used in the experiments to evaluate the performance of the proposed ACMP model.

The dataset used in the paper is Amazon clothing, Amazon-Electronics, and DBLP.

The dataset used in the paper is a collection of six low-homophily node classification tasks.

The dataset used in the paper is a collection of real-world benchmark datasets for node classification.

The dataset used in the paper is a citation network, specifically Cora, CiteSeer, PubMed, Coauthor-CS, and Coauthor-Physics.

The Coauthor Physics dataset is a co-authorship graph extracted from the Microsoft Academic Graph, with a focus on Physics research.

Tencent transaction dataset for node classification task, containing 6.49 million nodes and 33.63 million directed edges

Ethereum dataset for node classification task, containing 2.18 million nodes and 3.64 million edges

The dataset used in the paper is a citation graph dataset, which is used for node classification and link prediction tasks.

Node classification is the task of predicting the labels of unlabeled nodes in a graph. State-of-the-art methods based on graph neural networks achieve excellent performance...

Graph classification and node classification datasets

Graph classification and node classification datasets

Graph classification and node classification datasets

The ENZYMES dataset contains 600 proteins from each of the 6 Enzyme Commission top-level enzyme classes (EC classes) and the goal was to correctly predict enzyme class...

The IMM ATT UMIST, COIL USPS, and PIE datasets are used for node classification tasks.

The Cora and Citeseer datasets are used for training machine learning models to classify documents into different categories.