It is estimated that as of 2014, 38% of the human population had used the services of the internet in one way or another.
Today, there is an estimated one billion active websites on the World Wide Web and more than 3 billion web users globally.
These numbers keep increasing exponentially thanks to the increased worldwide internet connectivity.
The global computer network connectivity is heavily reliant on search engines that make it possible for users to access content that is displayed online.
Google search engine is the world’s most popular search platform. Founded 17 years ago, this internet giant has seen many improvements and updates that keeps it ahead of the rest by a noticeable margin.
The majority of Google users rarely understand the inner workings that miraculously display results when they search for content online.
The level of abstraction that the creators of Google have used enables users to interact with the system with ease without having to think about the underlying processes that analyze the words we type on the search bar and display the results for us on our device screens.
In this in post, we get the Google search algorithm explained. An in-depth look at how Google reads the queries and decides what results to display for the users. It will help us understand how millions of global web searches are attended to daily, ubiquitously.
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Google Search Algorithm
Think of an algorithm as a self contained step by step set of operations, usually written as a computer program or code, that aid in calculations and data processing.
Since its inception, Google relies on a written set of rules that define how to sieve through the huge heap of information from the vast internet data store, and pick information that is related to the users search words before displaying it on a webpage.
To the user, of course, the search engine seems to return results quite easily and fast, but in real sense, Google has done thousands of calculations behind the screens and processed though big volumes of data files from all over the internet to report on the most likely answers to the user queries.
Page rank was the first search algorithm used by Google to process search queries. Named after one of the founders of the company, Larry Page, it is the most widely known Google algorithm to date.
Google updates its search engine algorithms hundreds of times every year. Usually, minor changes are effected in those updates, and the cores of the algorithm remain largely untouched.
Occasionally though, Google rolls out major updates to its framework algorithm, affecting in a significant way how it’s search works.
How Google Search Works
There are approximately 60 trillion web pages on the Internet today, and the number continues surging upwards. When a user types in search terms on the browsers search box, the search engine reads the query and then navigates the World Wide Web through a process known as web crawling.
This essentially means that it follows web page links and sorts them out by their content. Google Bots are virtual Google web crawling robots that retrieve web pages related to the user’s search terms and hands them over to the search engine indexer.
Think of Google bots as search dogs that go out and sniff out for drugs hidden in cars, returning them once found to their handlers.
The search algorithm’s job is to get clues from the index for the engine to better understand what the user search terms mean.
When the web server sends a query to the index servers, the query accesses the files stored in the index. These are basically the files that were collected by the Google bots and their contents represent files that are similar to what the user searched for.
Snippets are then generated to describe each search result to be displayed. The contents are then returned back to the users interface as the Google search results.
So far, we know how the algorithm feeds the index pages that should be displayed as results. So what criteria does it use to select the relevant content to send to the indexer?
How Web Crawling Works
Google treats page links as votes, and considers some of the votes as more important than others.
Page rank goes through the links and classifies the more weighty links as important, based on their vote scores. It is these scores among several other factors that determine how web pages rank among themselves.
Pages that are ranked highly relative to the user search terms are more likely to be relayed back to the user as results.
Website programmers and online content creators rely on a number of techniques to ensure that their content is easily accessible to web crawlers to increase the number of visitors to their sites.
The whole idea of having a website or a blog is to have as many visitors as possible. One of the techniques they use to make is easy for the web crawler to access their web pages is site mapping.
Simply put, sitemaps present a path for page indexing necessary for Google search engine crawling robots. This protocol helps webmasters to relay to the search engine page URL’s in a website that are available for crawling.
This increases the chances of webmasters content being displayed to users whenever they search for information related to what the website is offering.
Site mapped pages are more likely to be identified and indexed for display whenever related queries are raised by the search engine.
There are several tools that assist webmasters create their website maps. Google offers this service free of charge.
Google Search Algorithm Updates
Google uses a horde of complex text mapping techniques such as keywords, domain name length and history among others, along with page rank to determine what to return as search results.
Page rank algorithm has gone through many changes both major and minor. Here are some of the notable major updates that have been made to the search algorithm over time to make it more efficient as the global top search engine.
- Google Pirate Update: As the name suggests, Pirate was released to curb copyright infringement. Websites with copyright related illegalities are prevented from ranking well by this algorithm filter.
- Google Panda Update: Introduced in February 2011, Panda is a search filter update that helped to prevent sites with poor quality content from ranking highly on page rankings.
- Google Penguin Update: Penguin was released in 2012 as a way to tame sites that were spamming the search results. It was an update that aided the search process by picking out those sites that used bad links to improve their rankings unfairly and forcing them to correct their actions.
- Google Hummingbird Update: 2013 saw this new search algorithm released to help the search engine pay more attention to query terms. Hummingbird paid more attention to whole search phrases and focused more on the meaning behind each word for more accurate results.
- Google Pigeon Update: On July of 2014, Pigeon was released to provide relevant and more refined local search results that are more closely tied to traditional web ranking signals. Pigeon helped to improve Google’s location and distance ranking functionalities.
In July of 2015, Google announced possible updates to its search algorithm. It was however quick to add that the update was a minor addition to the core search algorithm and would take several months to roll out.
Finding useful content online is something many web users take for granted. The nature of the internet allows us to interact with search engines without pausing for a moment to ask ourselves how Google fetches information from the web network.
With Google search algorithm explained, we can now understand the vital processes that take place whenever we type on our keyboards searching for information online.