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Google Launches Neural Matching Algorithm
The last couple of months have been pretty eventful when it comes to Google's organic rankings with its latest algorithm updates we see a more granular interpretation of pages and a strong emphasis on content vs context and intent.
What does the algorithm actually do?The purpose of the algorithm is to match a search query to a web page, using only the search query and the web page itself. Web pages ranked by this kind of algorithm will not have been promoted to the top positions by links or keywords since this kind of algorithm is about “relevance matching.”
Content is more importantSo why the need for neutral matching you ask? Simple, Google wants content to be the key driver of search relevance while other factors become less and less important over time.
What should we take from this update?This machine learning update isn't simply about matching keywords to content, but keyword intent expressed and matched it to content that matches the context of that expression.
“…we’ve now reached the point where neural networks can help us take a major leap forward from understanding words to understanding concepts. Neural embeddings, an approach developed in the field of neural networks, allow us to transform words to fuzzier representations of the underlying concepts, and then match the concepts in the query with the concepts in the document. We call this technique neural matching.”