Covers Probabilistic Information Retrieval, modeling relevance as a probability, query expansion, and automatic thesaurus generation.
Explores lexical semantics, word sense, semantic relations, and WordNet, highlighting applications in language engineering and information retrieval.
Covers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.
Covers Latent Semantic Indexing, a method to improve information retrieval by mapping documents and queries into a lower-dimensional concept space.
