Stream Reasoning

Stream reasoning focuses on efficiently processing and reasoning over continuous data streams, aiming to extract knowledge and insights in real-time. Current research emphasizes developing efficient algorithms and model architectures, such as multi-stream approaches and neural-symbolic integration, to handle high-volume, high-velocity data from diverse sources (e.g., sensor data, text, images). This field is significant for enabling real-time decision-making in applications ranging from robotics and IoT to natural language processing and large-scale data fusion, bridging the gap between symbolic and sub-symbolic reasoning methods.