Deformed Laplacians and spectral ranking in directed networks

© 2017 Elsevier Inc. Deformations of the combinatorial Laplacian are proposed, which generalize several existing Laplacians. As particular cases of this construction, the dilation Laplacians are shown to be useful tools for ranking in directed networks of pairwise comparisons. In the case of a connected graph, the entries of the eigenvector of the dilation Laplacians with the smallest eigenvalue have all the same sign, and provide directly a ranking score of its nodes. The ranking method, phrased in terms of a group synchronization problem, is applied to artificial and real data, and its performance is compared with other ranking strategies. A main feature of this approach is the presence of a deformation parameter enabling the emphasis of the top-k objects in the ranking. Furthermore, inspired by these results, a family of random walks interpolating between the undirected random walk and the Pagerank random walk is also proposed.

Jaar van publicatie:2019

BOF-keylabel:ja

IOF-keylabel:ja

BOF-publication weight:6

CSS-citation score:1

Authors from:Higher Education

Toegankelijkheid:Open