This research study investigates the minimization of inequality in the ranks of vertices obtained using the PageRank algorithm. PageRank is a widely used algorithm for ranking webpages and plays a significant role in determining web traffic. This study employs the Gini coefficient, a measure of income/wealth inequality, to assess the inequality in PageRank distributions on various types of graphs. The investigation involves two experiments: one that modifies strategies for handling dead-end nodes and another that explores six deterministic methods for reducing inequality. Our findings indicate that a combination of two distinct heuristics may present an effective strategy for minimizing inequality.

翻译：本研究探讨了在使用PageRank算法获得的顶点排名中不平等最小化的问题。PageRank是一种广泛用于网页排序的算法，在决定网络流量方面发挥着重要作用。本研究采用衡量收入/财富不平等的基尼系数，来评估各类图中PageRank分布的不平等程度。研究工作包含两个实验：其一调整了处理悬空节点的策略，其二探索了六种降低不平等的确定性方法。研究结果表明，两种不同启发式方法的组合可能成为实现不平等的有效最小化的策略。