Abstract: In light of the growing emphasis on the right to be forgotten of graph data, machine unlearning has been extended to unlearn the graph structures’ knowledge from graph neural networks (GNNs) ...

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

Abstract: Graph neural network is a new neural network model in recent years, whose advantage lies in processing graph structure data. In the era of big data, people can collect a large amount of ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

1 COSCO Shipping Technology Co., Ltd., Shanghai, China. 2 COSCO Shipping Specialized Carriers Co., Ltd., Guangzhou, China. The cost and strict input format requirements of GraphRAG make it less ...

Spatial-temporal data handling involves the analysis of information gathered over time and space, often through sensors. Such data is crucial in pattern discovery and prediction. However, missing ...

The Graph, the decentralized indexing system that works much like Google for blockchains, has introduced a data standard for Web3. Called GRC-20, the standard would define how information is ...

Ego-centric searches are essential in many applications, from financial fraud detection to social network research, because they concentrate on a single vertex and its immediate neighbors. These ...

The timely and accurate prediction of maize (Zea mays L.) yields prior to harvest is critical for food security and agricultural policy development. Currently, many researchers are using machine ...

1 College of Computer Science and Technology, University of Qingdao, Qingdao, China 2 Yunxiao Road Outpatient Department, Qingdao Stomatological Hospital, Qingdao, China Introduction: The automatic ...