Probabilistic models for topic detection and tracking

We present probabilistic models for use in detecting and tracking topics in broadcast news stories. Our information retrieval (IR) models are formally explained. The topic detection and tracking (TDT) initiative is discussed. The application of probabilistic models to the topic detection and tracking tasks is developed, and enhancements are discussed. We discuss four variations of these models, and we report our preliminary test results from the current TDT corpus.