算法与计算机科学patents.google.com
Google 的 PageRank 专利已过期
Google's PageRank patent has expired
2019 — 2022，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
这个页面是 Google 早期核心专利 PageRank（US6285999B1）的专利页，该专利已经过期。PageRank 用网页之间的链接结构来评估网页重要性，曾是 Google 搜索排序的基础信号。评论围绕它的历史作用、算法能否被专利化，以及它在现代搜索和神经科学中的后续应用展开。
为什么经久不衰：它既是搜索史的关键节点，又引出算法专利、链接分析和排名演进等长期议题；专利过期让这些讨论在今天仍有现实意义。
HN 评论精选
PageRank 被神话了，Google 的工程执行力和对用户/网络的贴合比单一算法更关键。
迷思：PageRank 是 Google 成功的秘密。事情没那么简单。它也许短暂地带来过差异，但大约六个月内，每个像样的搜索引擎都以某种形式实现了 page rank。对普通人来说这是个可爱的故事。现实中，当时的搜索已经是在平衡大量信号以形成不错的排名公式，比只应用某个神奇算法难得多。我认为当年构建 Google 搜索的人值得多得多认可。远胜任何算法公式的是 Google 的执行能力，以及以契合网络文化的方式执行。
bborud查看英文原文
Myth: PageRank was the secret to Google's success It wasn't really that simple. For a brief while, perhaps it made a difference, but within perhaps a span of 6 months, every decent search engine implemented page rank in one form or another. It is a cute story for the muggles to focus on. In reality search was already then about balancing a large number of signals into a decent ranking formula. It was much, much harder than just applying some magic algorithm and I think the people who built Google search back in those days deserve a lot more credit. But that wasn't really a sexy story, I guess. To a much greater degree than any algorithm or formula: Google's ability to execute, and to do so in cultural sympathy with the web, was more important. Much has been said about Google's Not Invented Here, but this made all the difference in the early days: you had to get things to where you could iterate and innovate fast. And I say that admiringly as someone who worked for one of their competitors at the time. I used to be jealous of Google because they were managed by people who were part of the Internet. Our management was alien to the Internet (and our business model was to power search for portals mainly run by horrible, stupid people in suits). Google was the only search engine that was properly in tune with its audience: focusing on the user. (Disclosure: I worked for FAST, then Yahoo, then Google until I quit Google in 2009)
从数学家视角看，算法类似数学定理，算法可专利化令人难以接受。
每隔一阵我就会想起算法居然可以被专利。随之而来的是恐惧和普遍的挫败无力感。然后我慢慢试图忘记这个事实，才能继续在这个疯狂世界里生活。作为数学家，我把算法视为定理的实例，给定理、给数学真理“申请专利”的想法太陌生了。
enriquto查看英文原文
Every once and then I remember that you can actually patent algorithms. Terror ensues, and a general feeling of frustration and helplesness. Then I try to forget this fact slowly, just to be able to continue living in this crazy world. As a mathematician, i see algorithms as examples of theorems, and the idea to "patent" a theorem, a mathematical truth, is so foreign!
PageRank 已被用于神经科学建模，连接性可用来表示重要性和稳定性。
我看到很多关于 PageRank 的计算机科学讨论，想给一个不太一样的视角。我在 CalTech 的同事最近用 PageRank 算法建模活体神经网络的演化。这个概念很适合建模简单 Hebbian 学习的扩展，并解释一些群体动力学（至少在海马体中）。学习相关网络在数周内会发生群体层面的动态变化，但有些神经元的放电方式/时间非常稳定；可以用 PageRank 之类方法对稳定性排序，说明连接性意味着重要性，也许还意味着稳定性。
whymauri查看英文原文
There's a lot of discussion I see about PageRank for CS purposes, so I'd like to give a slightly different perspective most people haven't heard about. A colleague of mine at CalTech recently used the PageRank Algorithm to model the evolution of in-vivo neural networks [0, page 8]. The concept is pretty good for modeling extensions of simple Hebbian learning and explaining some of the ensemble dynamics (at least in the hippocampus). If you're interested in further reading, there's more work on attractor states in biological learning and associative memory (some of which is cited in the paper). Brief overview: there's debate on whether brain network dynamics are stable or unstable. In networks related to learning and over the timespan of weeks, this experiment observed that ensemble-level dynamic change during learning but some neurons are remarkably stable in how/when they fire. You can rank stability with methods like PageRank, suggesting that connectivity implies importance (and perhaps stability). [0] https://www.biorxiv.org/content/biorxiv/early/2019/03/07/559104.full.pdf
PageRank 仍是基础排序信号，但现代搜索叠加了大量机器学习与细分领域权重。
我不确定这现在还有多大用处。Google 仍把它用于基础排序，但结果随后会经过多种附加机器学习流水线，比如 Vince（权威/品牌力）、Panda（入链质量）、Penguin（内容质量）等，以及其他针对页面布局、广告位置等属性的系统。还有更细粒度的权重，比如“细分领域内的力量”：新页面可能在管道行业表现不错（因为站点其他页面），但不会自动在医疗话题上有权威。
tyingq查看英文原文
I'm not sure how useful this might be to anyone anymore. Google still uses it for the base ranking. But, the results are then run through a variety of add-on ML pipelines, like Vince (authority/brand power), Panda (inbound link quality), Penguin (content quality), and many others that target other attributes (page layout, ad placement, etc). Then there's also more granular weightings for things like "power within a niche", where a new page might do well for plumbing (because of other existing pages on the site), but wouldn't automatically have any authority for medical topics.
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