Yi-Cheng Zhang

TL;DR: Interesting cooperation and competition patterns of the society seem to arise and to be responsive to the payoff function.

TL;DR: This work provides a creditable method for compressing bipartite networks, and highlights a possible way for the better solution of a long-standing challenge in modern information science: How to do a personal recommendation.

TL;DR: Kinetic interfaces form the basis of a fascinating, interdisciplinary branch of statistical mechanics as mentioned in this paper, which can be unified via an intriguing nonlinear stochastic partial differential equation whose consequences and generalizations have mobilized a sizeable community of physicists concerned with a statistical description of kinetically roughened surfaces.

TL;DR: Simulations on four real networks show that the proposed semi-local centrality measure can well identify influential nodes and is a tradeoff between the low-relevant degree centrality and other time-consuming measures.

TL;DR: This paper introduces a new algorithm specifically to address the challenge of diversity and shows how it can be used to resolve this apparent dilemma when combined in an elegant hybrid with an accuracy-focused algorithm.