network selection a method for ranked lists selection网络选择排名列表的方法选择.pdfVIP

Network Selection: A Method for Ranked Lists Selection 1,2 . 2. 3 Luisa Cutillo * , Annamaria Carissimo , Silvia Figini 1 Department of Statistics and Mathematics for the Economic Research, University of Naples ‘‘Parthenope’’, Naples, Italy, 2 Bioinformatics Core, Telethon Institute of Genetics and Medicine, Naples, Italy, 3 University of Pavia, Pavia, Italy Abstract We consider the problem of finding the set of rankings that best represents a given group of orderings on the same collection of elements (preference lists). This problem arises from social choice and voting theory, in which each voter gives a preference on a set of alternatives, and a system outputs a single preference order based on the observed voters’ preferences. In this paper, we observe that, if the given set of preference lists is not homogeneous, a unique true underling ranking might not exist. Moreover only the lists that share the highest amount of information should be aggregated, and thus multiple rankings might provide a more feasible solution to the problem. In this light, we propose Network Selection, an algorithm that, given a heterogeneous group of rankings, first discovers the different communities of homogeneous rankings and then combines only the rank orderings belonging to the same community into a single final ordering. Our novel approach is inspired by graph theory; indeed our set of lists can be loosely read as the nodes of a network. As a consequence, only the lists populating the same community in the network would then be aggregated. In order to highlight the strength of our proposal, we show an application both on simulated and on two real datasets, namely a financial and a