Description: Temporal Event Models are analytical approaches that focus on the representation and analysis of events occurring over time. These models allow capturing the dynamics of complex systems, where events not only occur in a static context but their occurrence and sequence can influence the behavior of the system as a whole. Often, these models integrate multiple modalities of data, such as text, audio, and video, enabling them to provide a richer and more comprehensive view of events. The ability to analyze temporal events is crucial in various disciplines, from engineering and computer science to social sciences and biology, as it allows researchers and professionals to understand patterns, predict future behaviors, and make informed decisions based on historical data. In summary, Temporal Event Models are powerful tools that facilitate the understanding of temporal complexity in multimodal systems, providing a framework for the analysis and interpretation of data that evolves over time.
