Often I find myself focusing on specific strategies to perform specific functions.
How do I write compelling copy torank on voice search?
What structured data produces easy wins?
Things like that.
These important questions are often covered here on Search Engine Journal in very useful articles.
But it’s important to not just understand what tactics might be working to help you rank. You need to understand how it works.
Understanding the structure that the strategy is functioning in is paramount to understanding not just why that strategy is working, but how and what it’s trying to accomplish.
Previously, we discussed how search engines crawl and index information.
This chapter will explore the basics of how search algorithms work.
What Is an Algorithm? A Recipe
If you ask Google what an algorithm is, you’ll discover that the engine itself (and pretty much everyone else) defines it as “a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.”
If you take anything from this definition, it’s critical to understand what it is not in our context here.
An algorithm is not a formula.
To wrap our heads around the difference, why it’s important, and what each does, let’s consider for a moment the meal I might place on my dinner plate tonight.
We’ll go with a favorite of mine:
- Roast beef
- Horseradish
- Yorkshire pudding
- Green beans
- Mashed potatoes
- Gravy
(That’s right, we Canadians eat more than poutine and maple syrup, though both are awesome though probably not together.)
The roast beef needs to be seasoned and cooked perfectly.
The seasoning combined with the roast would be an example of a formula – how much of each thing is necessary to produce a product.
A second formula used would be the amount of time and at what temperature the roast should be cooked, given its weight. The same would occur for each item on the list.
At a very basic level, we would have 12 formulas (6 items x 2 – one for measurements and the other for cooking time and duration based on volume) making an algorithm set with the goal of creating one of Dave’s favorite meals.
We aren’t even including the various formulas and algorithms required to produce the ingredients themselves, such as raising a cow or growing potatoes.
Let’s add one more formula though – a formula to consider the amount of different foods I would want on my plate.
So, we now have an algorithm to accomplish this very important task. Fantastic!
Now we just need to personalize that algorithm so that the rest of my family also enjoys their meal.
We need to consider that each person is different and will want different amounts of each ingredient and may want different seasonings.
So, we add a formula for each person. Alright.
An Algorithm of Algorithms
What the heck do a search algorithm and a dinner table have in common?
A lot more than you think.
Let’s look at just a few of the core characteristics of a website for comparison. (“Few” meaning nowhere near everything. Like not even close.)
- URLs
- Content
- Internal links
- External links
- Images
- Speed
As we witnessed with our dinner algorithm, each of these areas is divided further using different formulas and, in fact, different sub-algorithms.
It might be better if we think of it not as an algorithm, but as algorithms.
It’s also important to keep in mind that, while there are many algorithms and countless formulas at play, there is still an algorithm.
Its job is to determine how these others are weighted to produce the final results we see on the SERP.
So, it is perfectly legitimate to recognize that there is some type of algorithm at the top – the one algorithm to rule them all, so to speak – but always recognize that there are countless other algorithms and generally they’re the algorithms we think about when we’re considering how they impact search results.
Now, back to our analogy.
We have a plethora of different characteristics of a website being rated just as we have a number of food elements to end up on our dinner plate.
To produce the desired result, we have to have a large number of formulas and sub-algorithms to create each element on the plate and master algorithm to determine the quantity and placement of each element.
Sound familiar?
When we’re thinking of “Google’s algorithm” what we’re actually referring to is a massive collection of algorithms and formulas, each set to fulfill one specific function and gathered together by a lead or, dare I say, “core” algorithm to place the results.
So, we have:
- Algorithms like Panda to assist Google in judging, filtering, penalizing and rewarding content based on specific characteristics, and that algorithm likely included a myriad of other algorithms within in.
- ThePenguin algorithm to judge links and address spam there. But this algorithm certainly requires data from other pre-existing algorithms that are responsible for valuing links and likely some new algorithms tasked with understanding common link spam characteristics so the larger Penguin algorithm could do its job.
- Task-specific algorithms.
- Organizing algorithms.
- Algorithms responsible for collecting all the data and putting it into a context that produces the desired result, a SERP that users will find useful.
So there we have it. That’s how search algorithms work at their core.
Why Search Algorithms Use Entities
One of the areas of search that’s getting some decent attention lately, though which is under-emphasized, is the idea of entities.
For context, an entity is defined by Google as:
“A thing or concept that is singular, unique, well-defined and distinguishable.”
So, in our dinner analogy, there’s me. I’m an entity.
Each member of my family is also their own entity. In fact, my family unit is an entity unto itself.
By that token, the roast and each ingredient that goes into it are also their own entities.
So is the Yorkshire pudding and so is the flour that went into making it.
Google sees the world as a collection of entities. Here’s why:
At my dinner table, I have four individual entities that would have the state “eating” and a host of entities being consumed.
Classifying us all in this way has a lot of benefits to Google over simply assessing our activities as a series of words.
Each eating entity can now have assigned to them the entities that are on their plate (roast beef, horseradish, green beans, mashed potatoes, Yorkshire pudding but no gravy for entity xyz1234567890).
Google uses this type of classification to judge a website.
Think of each entity sitting at the table as a page.
The global entity that represents us all (let’s call this entity “Davies”) would be about “roast beef dinner,” but each individual entity representing an individual (or page in our analogy) is different.
In this way, Google can easily classify and judge the interconnectedness of websites and the world at large.
Basically, search engines aren’t responsible to just judge one website – they must rank them all.
The entity “Davies” is seen to be about “roast beef dinner” but the entity next door (let’s call this entity “Robinsons”) is about “stir fry.”
Now if an outside entity known as “Moocher” wanted to determine where to eat, the options can be ranked to Moocher based on their preferences or query.
Where (in my opinion) the real value in entities lies is in what happens the day after. We have some leftovers.
By processing the entity “roast beef” with a different formula and adding the entities bread, cheese, and onions, we have:
How Search Algorithms Use Entities
OK, it may not seem obvious how important this is in understanding search algorithms and how entities work in this way.
While understanding how Google seeing what a website is about as a whole has obvious value, you may be asking why it’s relevant for Google to understand that my roast beef and beef dip are related and in fact – are drawn from the same core entity.
Let’s consider instead Google understanding that a webpage is about roast beef. Let’s also consider that another page links to it and that page is about beef dip.
In this scenario, it’s incredibly important that Google knows that roast beef and beef dip are drawn from the same core entity.
They can assign relevance to this link based on the connectedness of these entities.
Before the idea of entities entered search, engines were left to assign relevance based on word proximity, density, and other easily misinterpreted and manipulated elements.
Entities are far more difficult to manipulate.
Either a page is about an entity or it’s not.
Through crawling the web and mapping common ways that entities relate, search engines can predict which relationships should carry the greatest weight.
So, How Do Search Algorithms Work?
Alright, we’ve covered a lot of ground and you’re probably getting hungry. You want some takeaways.
Context Matters
It’s important to understand how algorithms function to apply context to what you’re experiencing/reading.
When you hear of analgorithm update, it’s important to know that what is being updated is likely a small piece of a very large puzzle.
Knowing this assists in interpreting which aspects of a site or the world are being adjusted in an update and how that adjustment fits into the large objective of the engine.
Entities Are Super Important
Further, it’s critical moving forward to understand that entities:
- Play a massive role in search algorithms today.
- Have their own algorithms.
- Will play an ever-increasing role over time.
Knowing this will help you understand not just what content is valuable (how close are those entities you’re writing about?) but also which links are likely to be judged more favorably.
And that’s just to name a couple of advantages.
It’s All About User Intent
Search algorithms work as a large collection of other algorithms and formulas, each with its own purpose and task, to produce results a user will be satisfied with.
In fact, there are algorithms in place to monitor just this aspect of the results and make adjustments where ranking pages are deemed not to satisfy user intent based on how users interact with it.
Included in this are algorithms designed specifically to understand entities and how entities relate to each other in order to provide relevancy and context to the other algorithms.
Image Credits
Featured Image: Paulo Bobita
Define Algorithm Screenshot: Taken by author
Clock On Chalkboard:Adobe Stock&Adobe Stock
Google Algorithm Lesson:Adobe Stock
But Wait There’s More:Adobe Stock
Beef Dip:Adobe Stock
Next Chapter How Search Engines Rank Pages
Category SEO
FAQs
How search engine algorithms work everything you need to know? ›
When a search query is entered into a search engine by a user, all of the pages which are deemed to be relevant are identified from the index and an algorithm is used to hierarchically rank the relevant pages into a set of results. The algorithms used to rank the most relevant results differ for each search engine.
How are algorithms used in search engines? ›Search engine algorithms are computer programs that look for clues to give the searcher the exact results they are looking for. Search engines rely on algorithms to find web pages and decide which ones to rank for any given keyword.
How does a search engine works step by step? ›Search engines work by simply crawling billions of pages using the web crawlers they have developed. These are commonly referred to as search engine spiders or bots. A search engines spider then navigates the web by following links on a new web page it discovers to find new pages and so forth.
What is a search engine How does it work short answer? ›A search engine is a software program that helps people find the information they are looking for online using keywords or phrases. Search engines are able to return results quickly—even with millions of websites online—by scanning the Internet continuously and indexing every page they find.
What are the 10 algorithms one must know in order to solve most algorithm problems? ›- Dynamic Programming. ...
- Tree Traversal Algorithms. ...
- Graph Traversal. ...
- Linear Search. ...
- Binary Search. ...
- Bubble Sort. ...
- Insertion Sort. ...
- Selection Sort.
There are three basic stages for a search engine: crawling - where content is discovered; indexing, where it is analysed and stored in huge databases; and retrieval, where a user query fetches a list of relevant pages. PageRank is the best known algorithm which is used to improve web search results.
What are the 4 steps of algorithmic thinking? ›This broad problem-solving technique includes four elements: decomposition, pattern recognition, abstraction and algorithms. There are a variety of ways that students can practice and hone their computational thinking, well before they try computer programming.
What are the 4 types of algorithm? ›There are four types of machine learning algorithms: supervised, semi-supervised, unsupervised and reinforcement.
What are 3 examples of algorithms? ›Common examples include: the recipe for baking a cake, the method we use to solve a long division problem, the process of doing laundry, and the functionality of a search engine are all examples of an algorithm.
What are the basics of search engine? ›A search engine consists of two main parts: index and algorithms. To build its index, it crawls known pages and follows links to find new ones. The aim of search algorithms is to return the best, most relevant results. Search result quality is important for building market share.
What are the 3 components of a search engine? ›
In general, a search engine consists of three main components as shown in Figure 1: a crawler, an offline processing system to accumulate data and produce searchable index, and an online engine for realtime query handling.
What are the 3 basic types of search engines? ›There are three main types of search engines, web crawlers, directories, and sponsored links. Search engines typically use a number of methods to collect and retrieve their results. These include: Crawler databases.
How does Google get its answers? ›We continuously map the web and other sources to connect you to the most relevant, helpful information. We present results in a variety of ways, based on what's most helpful for the type of information you're looking for.
How does Google have all the answers? ›Google's system tracks all the information contained in the search index. In this step, duplicate content is canceled. All this information is stored in the Google Index and a large database is created. Serving Result: Whenever we type on Google to do some search, we get many answers related to our question as well.
What best describes a search algorithm? ›A search algorithm is the step-by-step procedure used to locate specific data among a collection of data. It is considered a fundamental procedure in computing. In computer science, when searching for data, the difference between a fast application and a slower one often lies in the use of the proper search algorithm.
How can I learn algorithms easily? ›- Have a good understanding of the basics.
- Clearly understand what happens in an algorithm.
- Work out the steps of an algorithm with examples.
- Understand complexity analysis thoroughly.
- Try to implement the algorithms on your own.
- Keep note of important things so you can refer later.
Important search algorithms include binary search and depth search. Must-know sorting algorithms include heap sort, merge sort, quick sort, number of inversions, and insertion sort. Hashing is also an important skill to learn that combines algorithms and data structures.
Which searching algorithm is most important? ›The binary search algorithm works on the principle of divide and conquer and it is considered the best searching algorithm because it's faster to run.
What are the five basic steps using search engine? ›- Keyword Selection. Keyword selection is the first step in search engine optimization. ...
- Use keywords in right position. Putting of keywords in the right position is much important as the selection of right keywords for a website. ...
- Content writing. ...
- Link Analysis. ...
- Avoid search engine spamming techniques and tools.
A search engine is a web-based tool that enables users to locate information on the World Wide Web. Popular examples of search engines are Google, Yahoo!, and MSN Search.
What are the 5 uses of search engines? ›
...
Search engines can be used to:
- To carry out research.
- To search for information about peoples, places and products.
- Get the definition of words, acronyms, etc.
- Download applications from the internet.
- To lookup other websites.
Unambiguity, fineness, effectiveness, and language independence are some of the characteristics of an algorithm. The scalability and performance of an algorithm are the primary factors that contribute to its importance.
What are algorithmic thinking skills? ›Algorithmic Thinking Definition. Algorithmic thinking is a derivative of computer science and coding. This approach automates the problem-solving process by creating a series of systematic logical steps that process a defined set of inputs and produce a defined set of outputs based on these.
What kind of problems are solved by algorithms? ›Algorithms can be designed for any type of problem, i.e. mathematical, logical, or any complex problems. Example: Depth-first-search, traveling salesman, sorting algorithms, etc. But, after some steps, the algorithm would result in a finite solution before ending.
What type of math is algorithms? ›Algorithms in Math
An algorithm in math is a procedure, a description of a set of steps that can be used to solve a mathematical computation. For example, a step-by-step procedure used in long divisions is a common example of a mathematical algorithm.
- Tying Your Shoes.
- Following a Recipe.
- Classifying Objects.
- Bedtime Routines.
- Finding a Library Book in the Library.
- Driving to or from Somewhere.
- Deciding What to Eat.
The simplest algorithm is to store the rules in a linked list in the order of increasing cost. A packet is compared with each rule sequentially until a rule that matches all relevant fields is found. This approach is storage efficient since it requires only O ( N ) memory locations.
What is the most famous algorithm called? ›The Merge Sort algorithm is by far one of the most important algorithms that we have today. It is a comparison-base sorting algorithm that uses the divide-and-conquer approach to solve a problem that once was a O(n^2). It was invented by the mathematician John von Neumann in 1945.
How to code an algorithm? ›- Step 1: Determine the goal of the algorithm.
- Step 2: Access historic and current data.
- Step 3: Choose the right models.
- Step 4: Fine tuning.
- Step 5: Visualize your results.
- Step 6: Running your algorithm continuously.
- Keyword Searching. Use a keyword search to search all parts of a source for the words you enter in the search box. ...
- Boolean Searching. ...
- Subject Searching. ...
- Limiters. ...
- Phrase Searching. ...
- Using References/Works Cited Lists.
What are the five 5 most commonly used search engine? ›
- Google.
- Bing.
- Yahoo!
- Yandex.
- DuckDuckGo.
- Baidu.
- Ask.com.
- Naver.
- Google Search usually ignores punctuation that isn't part of a search operator.
- Don't put spaces between the symbol or word and your search term. A search for site:nytimes.com will work, but site: nytimes.com won't.
The correct answer to the question “What technology do search engines use to 'crawl' websites” is option (d). Bots. These Bots crawl or index new web pages so that they could be searched on the internet, based on the keywords.
What is the difference between a browser and a search engine? ›Let's make it clear: A browser is a piece of software that retrieves and displays web pages; a search engine is a website that helps people find web pages from other websites. The confusion arises because, the first time someone launches a browser, the browser displays a search engine's homepage.
What is Google's search engine called? ›Google Search (also known simply as Google or Google.com) is a search engine provided and operated by Google. Handling more than 3.5 billion searches per day, it has a 92% share of the global search engine market.
What are the 5 basic information search techniques? ›- Keyword Searching. Use a keyword search to search all parts of a source for the words you enter in the search box. ...
- Boolean Searching. ...
- Subject Searching. ...
- Limiters. ...
- Phrase Searching. ...
- Using References/Works Cited Lists.
DuckDuckGo uses its web crawler, DuckDuckBot, and up to 400 other sources to compile its search results, including other search engines like Bing, Yahoo, and Yandex, and crowdsourcing sites like Wikipedia.
What is the most effective search technique? ›The answer is typically B - keywords and phrases. In most cases, you do not want to type in a long sentence or sentence fragment. Taking your search topic and translating it into the most important keywords that describe your topic is the most effective search technique.
What are the two basic search strategies? ›- Choosing search terms.
- Searching with keywords.
- Searching for exact phrases.
- Using truncated and wildcard searches.
- Searching with subject headings.
- Using Boolean logic.
- Citation searching.
8.4 How We Search: Information Searching (Querying) versus Browsing. The basic difference in approach can be summarized by comparing information searching or querying to browsing.
What is the golden rule of search engine optimization? ›
Promote the Likelihood of Quality Links
The search engine knows to rank any of your pages as extremely important if many authoritative pages externally (and within your site) link to it.
- Know Your Keywords.
- Write High Quality Content (Naturally)
- Use Keywords in Your Website Page URLs.
- Don't Overlook Page Titles.
- Review Every Page for Additional Keyword Placement.
- Improve User Experience.
- Hire an Expert.
A search engine normally consists of four components, that are search interface, crawler (also known as a spider or bot), indexer, and database. The crawler traverses a document collection, deconstructs document text, and assigns surrogates for storage in the search engine index.