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Rank aggregation


Suitable for

Mathematics and Computer Science
Computer Science
Mathematics and Computer Science, Part C
Computer Science, Part C


Description: In social choice theory, a general theme is to take a set of rankings of a set of candidates (also known as alternatives) and compile an "overall" ranking that attempts to be as close as possible to the individual rankings. Each individual ranking can be thought of as a vote that we want to compile into an overall decision. The project involves taking some real-world data, for example university league tables, and computing aggregate rankings to see which individual votes are closest to the consensus. In the case of the Kemeny consensus, which is an NP-complete rank aggregation rule, it is of interest to exploit heuristics that may be effective on real-world data, and see for how large a data set can the Kemeny consensus be computed.

Prerequisites: familiarity with polynomial-time algorithms, NP-hardness; interest in computational experiments on data