  We consider the problem of non-uniform vote aggregation, and in particular,
the algorithmic aspects associated with the aggregation process. For a novel
class of weighted distance measures on votes, we present two different
aggregation methods. The first algorithm is based on approximating the weighted
distance measure by Spearman's footrule distance, with provable constant
approximation guarantees. The second algorithm is based on a non-uniform Markov
chain method inspired by PageRank, for which currently only heuristic
guarantees are known. We illustrate the performance of the proposed algorithms
on a number of distance measures for which the optimal solution may be easily
computed.
