This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional Gated ...

Thus, we propose decoupled dynamic spatial-temporal graph neural network (DDSTGNN), a novel model designed to ... In addition, it integrates a dynamic graph learning module to model the evolving ...

Department of Applied Chemistry, School of Science and Technology, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan ...

The platform, which uses Django as the back-end service architecture and Echarts for knowledge graph visualization, has four modules: an antimicrobial-resistance predictive module, a pan-genomics ...

A second module uses a graph neural network to encode the generated molecular structure back into tokens for the LLMs to consume. The final graph module is a graph reaction predictor which takes ...

Python, Ruby, Rust, and Go. Long trusted as a reporter who prioritizes accuracy, integrity, and the best interests of readers, Paul is sought out by technology companies and industry organizations ...

Since Python has become the lingua franca of the programming world, there is not much room left for Ruby, he added. Overall, consolidation is happening in the programming language world ...

Therefore, to effectively utilize the information of the dynamic network and improve the prediction efficiency as well as the prediction accuracy, this paper proposes a spatio-temporal tensor graph ...