Basic Information
Advanced Probabilistic Retrieval Methods, Advanced Stochastic Language Modeling Techniques, Term-proximity Models, Results Diversification Models, The Axiomatic Approach to Retrieval, Learning to Rank, Information-theoretic Retrieval Models, The Risk-reward Paradigm, Rank-aggregation/fusion, Using Topic Models For Retrieval. Learning Outcomes# at The End of The Course The Student Will 1. Know How to Adapt and Apply The Matehamtical Models Taught In Class to New Problems, Be Able to Create Variants of The Models That Were Thught in Class For The Same Problems. 2. Design an Em Algorithm For Performing Soft Clustering. Example. 3. Design a Risk-reward Algorithm For Diversifying Search Engine's Results.