Google Brings In Bert To Improve Its Search Results

Google announced a forthcoming algorithmic update last week that will provide more relevant results for about 10 percent of search results queries. Google’s new algorithm works best for more conversational queries Google’s updated algorithm is termed as BERT (Bidirectional Transformer Encoder Representations).

BERT is based on the principles of neural networking and users will be able to perform detailed search queries with the voice assistant of Google as though they were speaking to real person.

BERT is a Natural Language Processing (NLP) model and helps the search results with written content of higher quality.

According to Google researchers, “unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers. As a result, the pre-trained BERT model can be fine-tuned with just one additional output layer to create state-of-the-art models for a wide range of tasks, such as question answering and language inference, without substantial task-specific architecture modifications.”

The news of the arrival of BERT and its impending impact has caused controversy in the SEO community. But the update of Google BERT is not designed to penalize any websites, but only to improve the understanding and interpretation of search queries by the search engine.

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