1996年，斯坦福大学的研究生Sergey Brin和Larry Page共同提出了PageRank算法 1。这一算法后来成为帮助Google成为家喻户晓名称的关键算法之一 1。
PageRank算法的核心原理是通过网页间的链接关系分配“声誉”来计算网页的重要性，即每个网页都拥有“排名”或声誉，并通过链接将声誉分享给其他网页 1。在文章提供的示例中，若BBC News的声誉为50并链接了5个页面，它会分配80%（即40分）的声誉，使得每个被链接的页面各获得8分 1。在具体的Python代码实现中，该算法的默认阻尼系数（damping）被设定为0.85，容差（tolerance）为1e-10 1。
An article reviews the background of the PageRank algorithm, which was proposed in 1996 by Sergey Brin and Larry Page when they were graduate students at Stanford University 1. PageRank is one of the key algorithms that helped Google become a household name 1.
The core principle of the algorithm is that each web page has a "rank" or reputation, which it shares with other web pages through links to calculate the importance of the pages 1. In an example provided in the article, BBC News has a reputation of 50 and links to five pages 1. It allocates 80 percent of its reputation, amounting to 40 points, to the outgoing links, meaning each of the five linked pages receives a score of 8 1.
The article also provides a simplified Python code implementation 1. The default damping coefficient in the code is 0.85, and the tolerance is 1e-10 1.
评论
还没有评论，欢迎留下第一条。