Google is making the largest change to its search system since the company introduced RankBrain, almost five years ago. The company said this will impact 1 in 10 queries in terms of changing the results that rank for those queries.
Rolling out. BERT started rolling out this week and will be fully live shortly. It is rolling out for English language queries now and will expand to other languages in the future.
Featured Snippets. This will also impact featured snippets. Google said BERT is being used globally, in all languages, on featured snippets.
What is BERT? It is Google’s neural network-based technique for natural language processing (NLP) pre-training. BERT stands for Bidirectional Encoder Representations from Transformers.
It was opened-sourced last year and written about in more detail on the Google AI blog. In short, BERT can help computers understand language a bit more like humans do.
When is BERT used? Google said BERT helps better understand the nuances and context of words in searches and better match those queries with more relevant results. It is also used for featured snippets, as described above.
In one example, Google said, with a search for “2019 brazil traveler to usa need a visa,” the word “to” and its relationship to the other words in query are important for understanding the meaning. Previously, Google wouldn’t understand the importance of this connection and would return results about U.S. citizens traveling to Brazil. “With BERT, Search is able to grasp this nuance and know that the very common word “to” actually matters a lot here, and we can provide a much more relevant result for this query,” Google explained.
Note: The examples below are for illustrative purposes and may not work in the live search results.
In another example, a search for “do estheticians stand a lot at work, Google Said it previously would have matched the term “stand-alone” with the word “stand” used in the query. Google’s BERT models can “understand that ‘stand’ is related to the concept of the physical demands of a job, and displays a more useful response,” Google said.
In the example below, Google can understand a query more like a human to show a more relevant result on a search for “Can you get medicine for someone pharmacy.”
Featured snippet example. Here is an example of Google showing a more relevant featured snippet for the query “Parking on a hill with no curb”. In the past, a query like this would confuse Google’s systems. Google said, “We placed too much importance on the word “curb” and ignored the word “no”, not understanding how critical that word was to appropriately responding to this query. So we’d return results for parking on a …read more
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