BERT stands for Bidirectional Encoder Representations from Transformers. BERT is Google’s New Search Algorithm Update after Rank Brain and It is the Neural network-based technique for Natural Language Processing (NLP). BERT tends to make the Search better for people across the globe. A powerful matter of these systems is that they can grasp the learnings from one language and apply them to other languages for better results.

 BERT to make Search better for people across the world. A powerful characteristic of these systems is that they can take learnings from one language and apply them to others. So we can take models that learn from improvements in English (a language where the vast majority of web content exists) and apply them to other languages. This helps us better return relevant results in the many languages that Search is offered in. For featured snippets, we’re using a BERT model to improve featured snippets in the two dozen countries where this feature is available and seeing significant improvements in more languages.

How It Works

Google explained that there are a lot of ways that it can understand what the language in your query means and how it relates to the content on the web. For example, if you misspell something, Google’s spelling systems can help find the right word to get you what you need. And/or if you use a word that’s a synonym for the actual word that it’s in relevant documents, Google can match those. BERT is just another signal or technique Google uses to understands language. Depending on what you search for, any one or combination of these signals could be more used to understand your query and provide a relevant result.