What is Neural Matching?
Neural matching is an algorithm used by Google to match words to concepts rather than just relying on keywords and links.
This development is a major step forward in understanding concepts and meaning and avoids giving high ranks to pages that are ‘spammed' with keywords and direct synonyms. Google calls this development “super synonyms.”
Google first introduced it in 2018, and it's used for 30% of total search queries.
The core concept of neural matching is to reward content creators for effectively answering the questions posed by user queries.
It's an example of how neural networks can help take a major leap forward from understanding words to understanding detailed concepts.
How does it work?
Neural Matching uses Google's latest AI technology to generate more diverse search results and is based on neural embeddings that extract underlying concepts of words.
It detects relationships between concepts by analyzing the use of words in context and identifying the specific idea or concept a user is searching for. This process allows Google to match a webpage to a query based solely on the text of the webpage rather than relying on singular keywords.