Credits: 4 (3-0-2)
Description
Retrieval models (Boolean, vector-space, probabilistic, language- model, Markov random fields, diversity-aware); Design of test collections (TREC, crowd-sourcing) and retrieval effectiveness measures (micro-/macro-F measure, nDCG, BPref); Collection models (multinomial repr.; topic mixtures) and topic modeling (LSA/LSI, LDA); Search engine architecture (crawling, indexing, and web-page ranking); Learning to rank; Knowledge graphs; Responsible IR (e.g., handling bias and fake-news, privacy, etc.).