超越Google的PageRank:基于复杂数字的节点排名计算

K. Sugihara
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引用次数: 3

摘要

本研究的重点是b谷歌的PageRank的替代算法,称为hermite centrality score,它采用复数对网络节点进行评分,以克服PageRank的链接分析问题。本研究提出了厄米中心性评分作为PageRank问题的解决方案,该问题与谷歌算法的阻尼因子有关。该算法不受阻尼因子的影响,能较好地再现PageRank结果。此外,该算法可以数学地、系统地改变网络节点的点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond Google’s PageRank: Complex Number-based Calculations for Node Ranking
This study is focused on a proposed alternative algorithm for Google's PageRank, named Hermitian centrality score, which employs complex numbers for scoring a node of the network to overcome the issues of PageRank’s link analysis. This study presents the Hermitian centrality score as a solution for the problems of PageRank, which are associated with the damping factor of Google’s algorithm. The algorithm for Hermitian centrality score is designed to be free from a damping factor, and it reproduces PageRank results well. Moreover, the proposed algorithm can mathematically and systematically change the point of a node of a network.
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