Detailed contents:

* Classical IR:

– formal IR models (Boolean, vector space, probabilistic and variants as BM25, Language models);

– structure of the inverted index (basics, compression);

– user interfaces for IR (classification, survey);

– classification (definition, naive Bayes classifiers)

– clustering (hierarchical and approximate algorithms);

– evaluation (foundations, methodologies, metrics; research topics).

* Web IR:

– Web graph (size and shape: small world and scale-free networks, bow-tie shape);

– link analysis for ranking and other applications (PageRank, HITS, variants);

– crawling (concepts and architecture);

– spam (short account);

– search engine architecture (short account).

* Case studies and specific issues.