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Google’s algorithm gets better at understanding your content, your website, its performance, and user’s search behavior. There are so many Google algorithms like Penguin, Panda, Hummingbird, Rankbrain, Bert, and many more. Some algorithms outperform others like SMITH which is a recent one and it seems to outperform BERT in terms of understanding lengthy content.
In this blog, we are going to compare the two algorithms in terms of their functioning and performance. As a digital marketer, you must understand how Google algorithms work because your SEO strategies depend on it. SEO agency in Bangalore analyses the latest algorithms and does a comparative study between them.
But first, here’s why Google uses BERT and/or SMITH
Most of the sites are composed of content in text form. To understand this content, Google uses algorithms.
When Google was first created, it had very simple algorithms that could not understand content much. It did not understand what else content should have other than keywords. It didn’t even know if the content made sense. Implementing Natural Language Processing (NLP) enables it to understand and also analyze the content.
BERT is the first algorithm to use bidirectional processing to define the meaning of a single word based on the contextual clues around it.
Bidirectional processing – A process of reading text in two directions – from left-right and right-left.
BERT has been regarded as the swiss army knife of NLP. It can understand different meanings of a word which helped Google understand your content better.
For example – The word to. BERT can differentiate to in “2 to 5” and “3 quarters to 5”.
To provide the users with the right content when they enter a search query, Google needs to understand and analyze thousands of content. These algorithms help it to do that and each new algorithm released precedes the previous one.
How BERT Google Algorithm works
BERT, as we said before, is a bidirectional Natural Language Processing. Being bidirectional is the best thing about it, as it makes understanding complex content structure easier. Since it can read in two directions, it can understand the relationship between the words next to each other and make sense of it.
This aspect of BERT makes the language processing more effective with lesser resource cost compared to the previous algorithms that came before it.
Another thing that makes BERT smart and effective is the application of its tokens. In layman’s terms, a token in an algorithm is an individual instance in a sentence, as opposed to class (types of words). For example, in the sentence – A car is a car, there are three classes which are “a”, “car” and “is” and five tokens, i.e, “a”, “car”, “is”, “a”, “car”.
More simply put, in a flock of birds, each bird is a token.
Now BERT has 30,000 tokens with additionals for fragments and characters. It can process the entire document within 256 tokens but beyond that, it stops functioning as the computing cost gets high. This is where Smith comes in, but let’s first understand why.
We’ve established that BERT processes your content based on each sentence. That means it understands the sentences word by word. Usually in a single sentence, sometimes incomplete, contains fewer connections between words and therefore there’s no clear idea to hold in memory. This is the reason the computing cost goes high after a point.
But, if you tried to understand the content by processing a chunk of it, by paragraphs, you’d get the whole point of it.
Now that’s what SMITH does.
What is SMITH algorithm and how it works
BERT uses 256 tokens per document but SMITH uses 2248 tokens for even longer documents. No wonder Google loves long content heavy with information and value. It processes the content in batches and offline too. Here’s how it understands your content –
- The entire document is broken down into chunks of sizes it can handle.
- SMITH then processes each para individually.
- A transformer then learns and understands the contextual meaning of the paragraphs and converts them into a representation of the document.
But that doesn’t mean that SMITH is completely independent of BERT. It still uses BERT’s help to understand the entire content. SMITH can also predict what the next sentences are going to be
Given its functioning ways and capabilities, SMITH does a better job than BERT but Google is still not clear on whether it’s using BERT or SMITH now.
Think about how we use search engines. Most of the time, our search queries are short. When you hit the search button, you’ll have to scroll down a bit to find exactly what you’re looking for.
Then what about content for long search queries?
With SMITH excellent at understanding the long search queries and the long-form documents, Google can now do its job better – providing the users with the exact information they need faster with a better user experience. It also outperformed BERT in terms of hierarchical attention, multi-depth attention-based hierarchical recurrent neural network, and more.
Conclusion
Understanding how Google algorithms works can help you create better content, and level up your SEO game. Researchers are hoping that maybe BERT and SMITH could work together so that the functioning of the two algorithms can be combined to be more productive and help Google understand the content better than before.
Whether Google is using SMITH or Bert, one thing remains the same. High-quality, relevant, and optimized content with updated SEO strategies always triumphs. If you’d like any SEO-related services, then these SEO services in Bangalore can help you out with the best solutions.
Webi7 is a leading SEO agency in Bangalore providing growth and results-oriented services to startups and small business owners. Do you want to improve your site’s rankings on the SERPs? Then contact to know more.
