Learn about cross-stream event detection methodologies in this comprehensive lecture that explores techniques for identifying and analyzing events across multiple data streams. Discover how to detect patterns and anomalies that span different information sources, examine the challenges of temporal alignment and correlation across heterogeneous data types, and understand the computational approaches used to process and analyze streaming data in real-time. Explore practical applications in areas such as social media monitoring, news analysis, and multi-sensor systems, while gaining insights into the theoretical foundations of event detection algorithms and their implementation considerations for large-scale data processing environments.