Discover the leading database management systems for enterprises in 2026. Explore key features, pricing, and implementation tips for selecting the best DBMS software to harness your data effectively.

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) ...

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 ...

Enterprises have long grappled with data dilemmas, from access management to security and hygiene. Those challenges are now amplified by the rush to add AI, a technology that hinges on a solid data ...

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 ...

Neo4j is the world's leading graph database, with native graph storage and processing.. Neo4j is the world's leading graph database, with native graph storage and processing.. Neo4j is the world's ...

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 ...

Graph learning focuses on developing advanced models capable of analyzing and processing relational data structured as graphs. This field is essential in various domains, including social networks, ...