Probabilistic Retrieval Models

This lecture discusses the Vector Space Retrieval Model, evaluating information retrieval, recall and precision tradeoff, F-Measure, accuracy metrics, precision/recall in ranked retrieval, and mean average precision. It also covers query likelihood models, language modeling, learning the model, and issues with Maximum Likelihood Estimation. The lecture further explores query expansion, user relevance feedback, the Rocchio Algorithm, and SMART algorithm for practical relevance feedback. Practical considerations and challenges in relevance feedback methods are also addressed.