What is the Name of Google Search Algorithm?

The earliest known Google search algorithm was PageRank. Larry Page and Sergey Brin created it in 1996 while studying at Stanford University.

PageRank ranked web pages by analyzing links. A link acted like a vote. However, not every vote carried the same value. Links from trusted websites had more weight than links from low-quality pages.

Over time, Google expanded far beyond PageRank. Today, Google Search uses hundreds of ranking systems, machine learning models, and relevance signals. 

For example, RankBrain, BERT, MUM, and Google’s core ranking systems all help improve search results. As a result, PageRank remains an important part of Google Search, but it is only one piece of a much larger ranking system.

The Origin of PageRank: The Original Google Search Algorithm

Larry Page created PageRank in 1996 during his Ph.D. research at Stanford University. Sergey Brin later joined the project and helped develop the idea into a working search engine.

“PageRank can be thought of as a model of user behavior.” – Larry Page & Sergey Brin, The Anatomy of a Large-Scale Hypertextual Web Search Engine (1998)

At the time, most search engines looked at keywords. PageRank looked at links. The idea was simple. A link from one page to another worked like a recommendation. However, not every recommendation had the same value. A link from an important page carried more weight than a link from an unknown page.

(Figure explaining the concept of PageRank where link equity was passed from pages to pages via backlinks.)

PageRank used a mathematical formula to assign every page a score. The score depended on three main factors:

• The number of pages linking to it.
• The importance of the linking pages.
• The number of outgoing links on each linking page.

The simplified PageRank formula is:

PR(A) = (1 − d) + d × Σ(PR(T) ÷ C(T))

Where:

• PR(A) = PageRank score of page A.
• d = Damping factor, usually 0.85.
• PR(T) = PageRank score of a linking page.
• C(T) = Number of outgoing links on that page.

The 0.85 damping factor represents the chance that a user follows another link instead of starting a new search. Google repeated the calculation many times until the scores became stable. Pages with higher scores were considered more authoritative.

Larry Page filed a U.S. patent for the technology in 1998. The patent is titled “Method for Node Ranking in a Linked Database” (US6285999B1). This is the original PageRank patent.

The patent explains a method for ranking documents in a linked database, such as the World Wide Web. Instead of counting keywords alone, it calculates a page’s importance from the quality and authority of pages linking to it. 

It also introduces the concept of a random surfer, who may either follow a link or jump to another page at random. That idea became the foundation of the PageRank formula and helped improve search quality by reducing spam and rewarding trusted pages.

Why PageRank Was Revolutionary

Before Google, search engines such as AltaVista, Lycos, Excite, and Infoseek looked mainly at page content. They counted keywords. They also checked titles, headings, and meta tags. As a result, many pages ranked well simply because they repeated the same words.

That system had a big weakness. Website owners could stuff pages with keywords. They could also hide text or fill meta tags with popular search terms. Therefore, many search results were poor.

PageRank solved that problem. It looked beyond the page itself. Instead, it examined links from other websites. Each backlink worked like a vote. However, every vote did not carry the same value. A link from a trusted website counted more than a link from an unknown page.

PageRank also passed only part of a page’s authority through each outgoing link. For example, a page with ten outgoing links shared its PageRank across all ten links. Google repeated the calculation many times. Then it updated the scores until they became stable.

Another advantage was scale. The algorithm could measure relationships across millions of web pages. As the web grew, Google could still rank pages quickly and accurately.

PageRank changed search forever. Content alone was no longer enough. Websites also needed quality backlinks from trusted sources. That idea still plays an important role in Google Search today.

Does Google Still Use PageRank?

“Yes, we do use PageRank internally, among many, many other signals. It’s not quite the same as the original paper. There are lots of quirks (eg, disavowed links, ignored links, etc.). We use a lot of other signals that can be much stronger.” – John Mueller, Google Search Advocate (2020)

Yes. Google still uses PageRank. However, it is no longer the main ranking system.

Google has confirmed that PageRank remains part of Google Search. In 2017, Gary Illyes said that PageRank is still used internally. In 2024, Google’s leaked API documents also contained references to PageRank-related signals. However, Google has not confirmed how much weight PageRank carries today.

PageRank now works with many other ranking systems. For example, Google also evaluates content quality, search intent, page experience, freshness, expertise, and helpfulness. Therefore, a page with many backlinks will not always rank first.

Google also retired the public PageRank Toolbar in 2016. Before then, website owners could see a PageRank score from 0 to 10 in their browsers. Today, Google no longer shares that score. Instead, it keeps PageRank as an internal ranking signal.

Although PageRank has changed over the years, its core idea remains the same. Links from trusted and relevant websites still help Google understand authority. As a result, earning high-quality backlinks remains an important part of SEO.

How Google’s Search Algorithm Has Evolved

Google’s search algorithm has changed a lot since its launch in 1998. At first, PageRank made backlinks one of the most important ranking signals. Today, backlinks still matter. However, Google evaluates them in a very different way.

Google no longer ranks pages with a single algorithm. Instead, many ranking systems work together. Each system evaluates a different signal before Google decides which pages appear in search results.

The process starts when Google crawls the web. Googlebot discovers new pages and revisits existing ones. Next, Google indexes pages that meet its quality standards. Only indexed pages can appear in search results.

When someone performs a search, Google first tries to understand the query. It looks at the meaning of the words, the search intent, the user’s location, language, and freshness needs. Systems such as RankBrain, BERT, and MUM help Google interpret complex searches.

Google then evaluates the most relevant pages. It considers hundreds of ranking signals, including:

• Content relevance to the search query.
• Search intent alignment.
• E-E-A-T signals.
• High-quality backlinks and link context.
• Page freshness.
• Page experience and Core Web Vitals.
• HTTPS security.
• Mobile-friendly design.
• Structured data and schema markup.
• Internal linking.
• Spam signals.

Google does not assign the same weight to every signal. The importance of each signal changes with the search query. For example, freshness matters more for breaking news. Backlinks may carry more weight for competitive topics. Local signals become more important for nearby businesses.

Finally, Google ranks the results. It continues to update those rankings as new pages appear, content changes, and its ranking systems improve. As a result, search results can change even when the search query stays the same.

Timeline of Major Google Algorithm Updates

Google has released hundreds of search updates since 1998. Some made small improvements. Others changed SEO for years. The timeline below highlights the most important milestones.

Year	Algorithm / Update	Why It Mattered
1996	PageRank	Introduced link analysis to measure page authority.
1998	Google Search Launch	Brought PageRank into Google’s public search engine.
2003	Florida	Reduced keyword stuffing and many early black-hat SEO tactics.
2005	Jagger	Improved link quality evaluation and targeted manipulative backlinks.
2009	Caffeine	Built a faster indexing system that allowed Google to discover new content more quickly.
2010	MayDay	Improved rankings for long-tail search queries and content quality.
2011	Panda	Lowered rankings for thin, duplicate, and low-quality content.
2012	Penguin	Penalized spammy backlinks and link schemes.
2013	Hummingbird	Improved Google’s understanding of natural language and search intent.
2014	Pigeon	Improved local search rankings using location and distance signals.
2015	Mobile-Friendly Update	Rewarded websites that worked well on mobile devices.
2015	RankBrain	Added machine learning to help process unfamiliar search queries.
2016	Possum	Improved local search results and filtered duplicate business listings.
2018	Medic Core Update	Increased the importance of content quality, trust, and expertise, especially for health and finance topics.
2019	BERT	Improved Google’s understanding of sentence context and word relationships.
2021	Passage Ranking	Allowed individual sections of a page to rank for relevant searches.
2021	MUM	Improved understanding across languages and multiple content formats.
2021	Page Experience Update	Added Core Web Vitals and page experience signals to ranking.
2022	Helpful Content System	Rewarded people-first content and reduced search-engine-first content.
2022	SpamBrain Expansion	Used AI to detect spam, link manipulation, and other abusive practices.
2023-Present	Core Updates	Continuously improve Google’s ranking systems across many search signals.
2024	AI Overviews	Added AI-generated answers for many search queries while linking to supporting web pages.

Common Myths About Google’s Search Algorithm

Many SEO myths have circulated for years. Some came from outdated practices. Others spread through forums and social media. Here are a few of the most common misconceptions.

Myth	Reality
Google uses one search algorithm.	Google uses many ranking systems, machine learning models, and search signals. There is no single algorithm that ranks every page.
More backlinks always improve rankings.	Google values link quality, relevance, and context more than the total number of backlinks. Many low-quality links may have little or no value.
PageRank is dead.	Google still uses PageRank internally. However, it is only one of many ranking systems.
Keywords alone can rank a page.	Google also evaluates search intent, content quality, E-E-A-T, backlinks, page experience, freshness, and many other signals.
Meta keywords improve rankings.	Google has ignored the meta keywords tag for web search rankings for many years.
Google penalizes every bad backlink.	Google often ignores spammy or low-value links instead of applying a manual penalty. Manual actions usually target deliberate link manipulation.
Publishing more pages guarantees higher rankings.	Content quality matters more than content volume. A few helpful pages often perform better than hundreds of thin pages.
Duplicate content leads to a Google penalty.	Duplicate content does not usually trigger a penalty. Instead, Google tries to identify the best version and may filter similar pages from search results.
AI-generated content cannot rank.	Google evaluates content based on helpfulness and quality, not on how it was created. Useful AI-assisted content can rank well.
Once a page ranks, it stays there.	Rankings change constantly. Google updates its index, refreshes ranking systems, and competitors publish new content every day.

Understanding how Google actually works helps you avoid outdated SEO tactics. It also helps you spend time on changes that improve long-term search performance instead of chasing myths.

Frequently Asked Questions About Google’s Search Algorithm

How often does Google update its search algorithm?

Google updates Search every day. Most changes are small. Google also releases several Core Updates and Spam Updates each year. Those updates can change rankings across many websites.

Can anyone see Google’s complete search algorithm?

No. Google has never shared its complete search algorithm. It also does not reveal the weight of each ranking signal. Instead, Google publishes patents, research papers, and Search Central documentation.

Why do search rankings change without warning?

Google constantly updates its index and ranking systems. Competitors also publish new content and earn new backlinks. As a result, rankings can change at any time. A Core Update is only one possible reason.

Do Google Search Quality Raters decide website rankings?

No. Quality Raters cannot change search rankings. They review sample search results. Google then uses their feedback to improve future ranking systems.

Where does Google announce major search algorithm updates?

Google announces major updates through Google Search Central. It also posts updates on the Google Search Central Blog and its official social media accounts. Many updates also appear on the Google Search Status Dashboard.