How Google is Refining the Search Results with the New BERT Model?

For better user experience and best results, Google always comes with new updates. This time its BERT (Bidirectional Encoder Representations from Transformers) that process words in relation to other words in a sentence. It has been claimed that it is one of the biggest steps for search in the last 5 years. Initially, it will be used on 1 in 10 searches in the US in English because of the complexity of this model. BERT model will improve the results in all of the two dozen countries where featured snippets are available. Before introducing this complicated model, it has gone through different testing phases and shown convincing results that have refined the search results. By understanding the connection between the words it has helped the algorithm in a better way.


With this change, Google aims to improve the understanding of queries, deliver more relevant results, and get searchers used to enter queries in a more natural way.

Google did not say to what extent this change will affect search rankings. Given that BERT is only being used on 10% of English queries in the US, the impact should be minimal compared to a full-scale algorithm update.

Understanding language is an ongoing challenge, and Google admits that, even with BERT, it may not get everything right. Though the company is committed to getting better at interpreting the meaning of queries.

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