Lecture
This lecture introduces Probabilistic Information Retrieval, focusing on the Query Likelihood Model, Language Modeling, and Probabilistic Language Models. It covers the probability of query relevance, language model generation, and smoothing techniques for non-occurring terms. The instructor discusses issues with Maximum Likelihood Estimation, the importance of smoothing, and the computation of document relevance probabilities. Examples are provided to illustrate the concepts, comparing Vector Space and Probabilistic Retrieval models.