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We consider the problem of rank aggregation based on new distance measuresderived through axiomatic approaches and based on score-based methods. In thefirst scenario, we derive novel distance measures that allow for discriminatingbetween the ranking process of highest and lowest ranked elements in the list.These distance functions represent weighted versions of Kendall's tau measureand may be computed efficiently in polynomial time. Furthermore, we describehow such axiomatic approaches may be extended to the study of score-basedaggregation and present the first analysis of distributed vote aggregation overnetworks.

Novel Distance Measures for Vote Aggregation