Google Update affecting the rankings: –
An overview of Google’s history of flagging and adjusting its updates and how this should inform a response to ranking changes.
A life cycle for a Google update is the introduction of a new algorithm, modifications to improve it, eventual obsolescence, and then replacement.
Improvements to the update generally begin shortly after the update is released and problems are identified.
Almost all Google updates roll back a bit, sometimes in the space of days, as if different parts were added unevenly across data centres.
The search results immediately after an update announcement are reversed in a few days for some sectors of the web, while they remain the same for others.
There are some algorithm updates that affect search results in a profound way, such as the 2018 Medic update and the most recent BERT update.
Transformers Bidirectional Encoder Representations is a transformer-based machine learning technique for natural language processing.
Google released BERT in open source on the GitHub platform.
Google itself used BERT in its search engine.
Adoption of BERT in the search algorithm.
Google BERT is an algorithm that increases the understanding of human language by the search engine.
BERT works both ways: it parses the context to the left and right of the word.
Another difference is that BERT builds a language model with a small text corpus.
While other models use large amounts of data to train machine learning, BERT’s bidirectional approach allows you to train the system with greater precision and with much fewer data.
This provides a much deeper understanding of the relationships between terms and between sentences.
This is essential in the search universe since people spontaneously express themselves in search terms and page content, and Google works to make the correct correspondence between one and the other.
Google had already adopted models for understanding human language, but this update was heralded as one of the most important advancements in search engine history.
Those updates had a huge impact on how Google understands search queries and website content.
The main updates, in general, have to do with relevance and general quality and could be the introduction of new algorithms or the same algorithms, but faster or improved.
In the early days of Google, the search index was updated monthly.
Each month, Google would aggregate the previous month’s crawl data and recalculate the rankings.
Google has started announcing when an update has finished rolling out.
If the rankings have changed and have not returned, now is a good time to take a closer look at overall quality and relevance.
Some of BERT’s capabilities may seem similar to Google’s first artificial intelligence method for understanding queries, RankBrain.
But they are two separate algorithms that can be used to report search results.
NLP is an area of artificial intelligence that converges with linguistics by studying the interactions of human and computational languages.
The intention is to fill the gaps between one language and another and make them communicate.
Like BERT, RankBrain also uses machine learning but does not process natural language.
The method focuses on query analysis and grouping of words and phrases that are semantically similar but cannot understand human language on their own.
So, when a new Google query is made, RankBrain analyzes previous searches and identifies which words and phrases best match that search, even if they don’t exactly match or have never been searched.
As they receive signals from user interaction, bots learn more about word relationships and improve ranking.
In the BERT announcement, Google also said that the update would affect featured snippets, which are the highlighted sections that appear in the “zero position” of the SERP.
Google began selecting the most relevant snippets for searches.
