Latest Google Algorithm Update: Google BERT

Google BERT

In the past many years, we have seen how Google changed the way people browse on the internet and through their several algorithms they helped users to frequently search on Google and find what they are actually looking for. Whether its Penguin, Panda, Pigeon, Hummingbird, Rankbrain, Possum or Fred all algorithms have made browsing easier. And now, here is another major update for us, its “BERT models”. People are curious to know what new we are going to see this time by Google BERT update.

So, we all have these questions, especially all SEO experts: professionals who need to modify their digital marketing strategies on timely manner-

  1. What exactly BERT models are? and,
  2. What additional it is going to offer us in searching? 

Let’s discuss more. 

What are BERT Models?

On 25th Oct, Pandu Nayak from Google, explained all of us about BERT and how its going to help user search better. According to Nayak, last year Google was introduced neural network-based technique for natural language processing (NLP) pre-training called Bidirectional Encoder Representations from Transformers which is termed as BERT.

With the help of this technology anyone can train their own state-of-the-art question answering system. 

This is basically the result of latest advancement of Google research, on transformers: models. Generally in Google search they process words in relation to all the words in a sentence instead of processing them one-by-one in order. 

That’s why here comes BERT models, that will consider the full context of a word by considering all the words that come before and after it. It will help in understanding the intent behind the search queries made by users on search bar. 

How BERT Models apply to Search

Sometimes, users are not clear about what should they write as “keyword” to search for their specific needs, so they write text in search bar around with what they are looking for.

Google BERTIt makes Google display irrelevant results too which are not as per user interest. To make the search easier and for understanding user perspective, BERT is introduced. 

The more natural you are the more accurate Google results will be!

From now on, whatever we search on Google, prepositions we use will pay a major role. Particularly for longer, more conversational queries, or searches where prepositions like “for” and “to” matter a lot to the meaning, Search will be able to understand the context of the words in your query. It means, you can search in a way that feels natural for you. 

Let’s Understand it by Example

Nayak shared an example to understand BERT better, like, there was a search “2019 Brazil travelers to USA need a visa.” Here the prepositions “to” used is having a relationship with the other words used in the search query and its particularly important to understand the essence.

It’s basically about a Brazilian traveling to the U.S., and nothing else to look after. With previous algorithms, it’s not clear to understand the meaning of this search query. So, Google may result about U.S. citizens traveling to Brazil which is irrelevant with what user is looking for. 

With BERT, preposition “to” will help Google to understand the meaning and provide a much more accurate results of this query.

Conclusion

To conclude this article, what we understood is BERT Models are helpful for Google search results and, whatever words we write in search bar models will understand the intent of the search queries we apply, and will display results according to it. 

BERT models are certainly the game changers in NLP and now this is the time where machines can better understand, speech and respond intelligently in real time.

Let us know about your thoughts on this article!