Link Stream

"Link stream" research focuses on analyzing sequences of temporal interactions, aiming to extract meaningful patterns and insights from dynamic data. Current research emphasizes developing efficient algorithms and models, including those based on deep learning (e.g., transformers, reinforcement learning), to handle the challenges of high-volume, evolving data streams, often incorporating techniques like attention mechanisms and streaming architectures for improved performance and interpretability. This field is significant for its broad applicability across diverse domains, from robotic control and network monitoring to natural language processing and environmental modeling, enabling more effective analysis and prediction in dynamic systems.