The BERT Algorithm (Bidirectional Encoder Representations from Transformers) is an AI-powered language model developed by Google. Introduced in 2019, BERT is designed to improve natural language understanding in searches, allowing search engines to better understand the full context of a word within a sentence.
Unlike traditional algorithms that analyze words in a sequence, BERT considers all words in the sentence simultaneously, allowing it to understand bidirectional context. This is especially useful for interpreting the more complex and longer search queries that users type.
For example, before BERT, if a user searched for “how to catch a fish without pain,” the search engine might have focused on the keywords “fishing” and “fish,” without fully understanding the nuance of “without pain.” With BERT, Google can understand that the user is interested in fishing techniques that do not cause pain to the fish.
For content creators and SEO specialists, this means it’s now more important than ever to write high-quality, relevant content that clearly and directly answers users’ questions. Rather than focusing exclusively on keywords, content should be geared toward user intent and provide comprehensive, useful answers.
