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pagerank js实现

2026-03-15 12:01:20JavaScript

PageRank算法概述

PageRank是一种用于衡量网页重要性的算法，基于链接结构分析。核心思想是：被越多高质量网页链接的网页，其重要性越高。

JavaScript实现PageRank

初始化参数设置

const dampingFactor = 0.85; // 阻尼系数
const maxIterations = 100; // 最大迭代次数
const tolerance = 0.0001; // 收敛阈值

构建链接矩阵

function buildGraph(links) {
  const graph = {};
  // 初始化所有节点
  links.forEach(link => {
    if (!graph[link.source]) graph[link.source] = {outLinks: [], inLinks: []};
    if (!graph[link.target]) graph[link.target] = {outLinks: [], inLinks: []};
  });

  // 填充链接关系
  links.forEach(link => {
    graph[link.source].outLinks.push(link.target);
    graph[link.target].inLinks.push(link.source);
  });
  return graph;
}

PageRank核心计算

function calculatePageRank(graph) {
  const nodes = Object.keys(graph);
  const N = nodes.length;
  let ranks = {};

  // 初始化均匀分布
  nodes.forEach(node => {
    ranks[node] = 1 / N;
  });

  for (let iter = 0; iter < maxIterations; iter++) {
    const newRanks = {};
    let totalDiff = 0;

    nodes.forEach(node => {
      let sum = 0;
      graph[node].inLinks.forEach(inNode => {
        sum += ranks[inNode] / graph[inNode].outLinks.length;
      });
      newRanks[node] = (1 - dampingFactor) / N + dampingFactor * sum;
    });

    // 检查收敛
    nodes.forEach(node => {
      totalDiff += Math.abs(newRanks[node] - ranks[node]);
    });

    ranks = newRanks;
    if (totalDiff < tolerance) break;
  }

  return ranks;
}

使用示例

const links = [
  {source: 'A', target: 'B'},
  {source: 'A', target: 'C'},
  {source: 'B', target: 'C'},
  {source: 'C', target: 'A'}
];

const graph = buildGraph(links);
const pageRanks = calculatePageRank(graph);
console.log(pageRanks);