Temporal modeling is a research area that focuses on analyzing and representing the temporal aspects of data, such as the sequence of events, changes over time, and patterns of behavior. This area involves techniques for capturing temporal dependencies, predicting future events, and understanding the dynamics of systems over time. Temporal modeling is used in various fields such as machine learning, data mining, natural language processing, and finance to make predictions and gain insights from time-series data.