RankBrain
Google's first machine-learning ranking system, introduced in 2015, which helps interpret how queries relate to concepts, especially…
Algorithms
Neural matching
A Google system that uses neural networks to understand how queries relate to page concepts, bridging vocabulary gaps between what users type and how pages are written.
In full
Google has described neural matching as a 'super-synonym' capability operating at the concept level, distinct from BERT's focus on the grammatical relationships within a query. Together they mean that a page need not contain a query's phrasing to be recognised as relevant. Neural matching is applied to both queries and pages, and is listed among current ranking systems.
Example
A query about 'why does my TV look soap opera-ish' surfaces pages explaining motion interpolation, a term the query never uses.
Related terms
BERT
A transformer language model Google applied to search from 2019, improving understanding of word order, prepositions and context within…
Semantic search
Retrieval based on the meaning of a query and documents rather than literal keyword matching, using entities, context and learned…
Google ranking systems
Google's documented list of the systems that generate rankings, distinguished from one-off 'updates' to those systems, and including…
Embedding
A numerical vector representing the meaning of text, an image or another item, positioned so that semantically similar items lie close…