Google has come up with a new algorithmic update called BERT. This new update will allow Google to understand natural language better, specifically in the field of conversational search.
It is estimated that BERT will influence around 10 % of queries, organic rankings along with featured snippets. Many of the marketers believe that this algorithm update will not be any small change but a transformational evolution.
However, are you aware of the fact that BERT is not just an algorithmic update, but can be called a categorized framework for machine learning, research paper, and natural language processing framework? Digital agencies across the world are keeping a close eye on their implementation process.
What does BERT in Search Mean?
BERT which stands for Bidirectional Encoder representations. It is the famous newly updated Google algorithm framework/tool which aims to evolve search options to minutely understand the context of words for better synchronization with queries for helpful results.
The unique thing about BERT is that it is an open-source academic paper. In the year 2018, the first paper was published under the name BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, authored by Jacob Deblin, Kenton Lee, Ming-Wei Chang, and Kristina Toutanova.
BERT is also a Natural Language Processing(NLP) framework by Google which is open-sourced for the natural language processing research field to take place.
Over the internet, the mention of BERT is not just a Google algorithm update but is considered as an actual research paper. More than anybody else, NLP and machine learning communities are elated about BERT as it takes a huge chunk of research in terms of natural language processing.
BERT has been pre-trained on various words and about 25,00 million words from English Wikipedia. With BERT being pre-trained on Wikipedia, it also includes answer datasets along with questions.
One of the examples of such question and answer data sets is called MS MARCO: A Human Generated Machine Reading Comprehension Dataset built and open-sourced by Microsoft.
Researchers are also competing over natural language understanding through SQuAD( Stanford Question Answering Dataset). BERT now is an evolution that can beat the human reasoning benchmark on SQuAD.
Some of the major AI companies who are also building up on BERT versions include Microsoft’s BERT called MT-DNN(Multi-Task Deep Neutral Network), RoBERTa from Facebook, SuperGLUE Benchmark, etc.
What are the problems BERT can solve?
- Solving The Puzzle Around Words
There exist some of the things that humans tend to understand easily which machines tend to ignore, not to forget the search engines as well. First and foremost, the problems with words are, they are scattered everywhere. More and more content is uploaded on the web every minute.
During this process, understanding of different words become problematic as they are ambiguous, polysemous, and have synonyms. BERT is designed in such a way so that it can solve ambiguous phrases and sentences, formed out of multiple meanings.
- Polysemy and Ambiguity
Almost every little or big word in the English language has different meanings. While speaking, it’s even worse because of the presence of prosody and homophones. It seems pretty challenging when it comes to similar pronunciation as four candles and fork handles for someone with a similar accent. This does not go well with the conversational search in the future.
- Context of Words
Any particular word has no meaning if it is not in sync with a particular context. The meaning of the word can change over the multiple parts of speech in the given context. Therefore, they may occur or the usability of various words depends upon which context people are using it for. The longer the sentence, it becomes difficult to track different parts of the speeches within the sentences.
How does Google BERT Work?
Google BERT can help Google Search engine to respond to the queries of the users who searched for different information. It will not only help to understand subtle nuances but will also enhance the search query better than ever before.
Few things upon which Google’s BERT will work upon are-
- It will accelerate the functionality of the Google search engine. In terms of search engine competition, it will have an edge over other search engines who aren’t using the BERT technology.
- Since through Google’s BERT, Google will be able to understand users’ search intentions. it would now present more relevant results to benefit the users via a digital agency.
- Eventually, it will cut down the amount of time spent on online browsing by the users through the search engine results pages.
What Content Creators and SEO’s can do?
As a Content Creator or SEO Manager one needs to make sure Google BERT does not influence the web search negatively in terms of search engine rankings. Few steps to keep in mind for Google BERT are as follows-
- Google BERT’s work is to help the users get relevant results they are searching for. Therefore, for SEO and content creators, it is important to understand who the audience is, and what they are searching for. Understanding your target audience seems critical in terms of searches and rankings.
- Once understanding the targeted audience is done, the next step is to come up with detailed and extremely beneficial content for the website visitors. Comprehensive Content is the need of the hour for a better understanding of the user’s intention.
- The next essential thing is to religiously follow the Google web master’s quality guidelines along with E-A-T content guidelines to ensure not to do something which Google explicitly prohibits.
Last but not least as mentioned earlier SEO practices will not be the same anymore, all thanks to Google BERT. Digital agencies will now try to come up with the rethinking of previously conditioned search engine fundamentals. The aim is to produce excellent content keeping in mind the needs of the targeted audience with the right keywords in the right place.
Google’s BERT will be the next big thing in search engine evolution and will play a big role in understanding online queries and present web results to online users.