Google officially announced on December 9, 2019, that their BERT algorithm was being deployed for seventy-two other languages besides English. Previously, Google announced in October the implementation of BERT for English language results, and expansion to more languages came naturally, although the process started faster than most analysts expected.
BERT is short for Bidirectional Encoder Representations from Transformers and is an algorithm created using neural networks, whose ultimate goal is to recognize patterns in user searches. Google made the BERT algorithm open-source in 2018, and now it has finally been integrated into the search engine’s services. It should also be noted that Bing has been using the pattern recognition offered by BERT in search results even before Google.
Google said during the October rollout that about 10% of all English language queries would be affected by this update, so it is expected that about the same percentage will affect searches in the seventy-two languages named by Google in this December rollout. Since BERT will not only focus on the English language, it will also affect the results of international featured snippets and will lead to volatility changes for sites that previously benefited from organic results in the search engine pages. However, the effect shouldn’t be drastic.
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BERT is not a regular Google algorithm update but a neural network that aims to recognize patterns in user queries, which can be crucial for identifying the meaning of different paragraphs in the indexed text. Google said BERT had been its core algorithm’s most significant step forward in the last five years. A single sentence can have multiple meanings that, to a human, may seem trivial, but various meanings were a challenge for most algorithms until BERT arrived on the market. Google’s algorithm changes have recently centered around machine learning and neural networks. But what exactly is a neural network?
Neural networks, in a nutshell, are a form of artificial intelligence in which an algorithm is trained to recognize patterns in particular objects in a way similar to how the human brain works. With the adoption of BERT, Google is taking an essential step in developing the algorithms needed to understand the search pattern behind any search. The novelty behind BERT is how it can be trained. Compared to other standard algorithms, BERT is not limited by the sequential order of words but can interpret a text in a bidirectional manner.
The best idea to always be in tune with the latest algorithm changes implemented by Google is to call on a professional company like GAMIT to design a detailed SEO optimization plan for you and to closely monitor all the elements that could influence your position in the SERPs.
Nevertheless, the effect of BERT’s implementation on search ranking seems to have been relatively minimal. BERT does not replace the existing algorithms used by Google but works together with them, so increased volatility in the SEO sphere outside of international featured snippets was not expected and has not occurred.
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