Within the class there were two versions of a given test; however, these two versions were just problem permutations of each other. The results above are all for the first of these two permutations. The two classes each had different tests which were variants of each other, testing the same learning outcomes.

LO1 (Learning Outcome 1) -- Code a basic inverted index capable of performing conjunctive queries.

LO2 -- Be able to calculate by hand on small examples precision (fraction relevant results returned), recall (fraction of results which are relevant), and other IR statistics.

LO3 -- Be able to explain where BM25, BM25F and difference from randomness statistics come from.

LO4 -- Give an example of how a posting list might be compressed using difference lists and gamma codes or Rice codes.

LO5 -- Demonstrate with small examples how incremental index updates can be done with log merging.

LO6 -- Be able to evaluate search results by hand and using TREC eval software.

LO7 -- Know at least one Map Reduce algorithm (for example to calculate page rank).

N/A -- Important material covered in the course but not directly related to a specific learning outcome.