Google ranking systems
Posted: Wed Feb 19, 2025 6:41 am
Google distinguishes between the following ranking systems:
AI ranking systems
Rankbrain
BERT
MUM
crisis information systems
deduplication systems
exact domain matching system
Freshness system
system for helpful content
link analysis systems and PageRank
Local messaging systems
Neural matching
original content systems
Distance-based downgrading systems
Page Experience System
passage ranking system
product rating system
system for reliable information
system for page diversity
spam detection system
Eliminated systems
Hummingbird (has been further developed)
Mobile friendly ranking system (now part of the Page experience system)
Page Speed System (now part of Page Experience System)
Panda system (part of the core system since 2015)
Penguin system (part of the core system since 2016)
Safe Sites System (now part of the Page Experience System)
These ranking systems are used in various process steps of the Google search.
Deep learning models and other components for ranking
According to statements by Google's Pandu Nayak in the 2023/2024 antitrust proceedings, Google uses the following deep learning models and components for ranking.
What is Rankbrain?
Google RankBrain is an artificial intelligence algorithm netherlands cell phone number list that is part of Google's search engine algorithm and was introduced in late 2015. Its main task is to better understand search queries and improve search results, especially for new, unique or complex queries that Google did not previously know about.
RankBrain uses machine learning to identify patterns in search queries and understand the meaning behind words. It aims to interpret the intent behind a search query to deliver more relevant search results, even when the exact words of the query are not present on the web pages. This makes RankBrain particularly effective at handling vague or ambiguous search queries.
An interesting feature of RankBrain is its ability to self-improve. It continuously learns from search queries and user click behavior to refine its algorithms and increase the accuracy of search results.
Rankbrain is only applied to the first 20-30 documents and adjusts the initial scores of that content. Since Rankbrain is very expensive, it is only used to pre-select documents with the highest initial scores.
AI ranking systems
Rankbrain
BERT
MUM
crisis information systems
deduplication systems
exact domain matching system
Freshness system
system for helpful content
link analysis systems and PageRank
Local messaging systems
Neural matching
original content systems
Distance-based downgrading systems
Page Experience System
passage ranking system
product rating system
system for reliable information
system for page diversity
spam detection system
Eliminated systems
Hummingbird (has been further developed)
Mobile friendly ranking system (now part of the Page experience system)
Page Speed System (now part of Page Experience System)
Panda system (part of the core system since 2015)
Penguin system (part of the core system since 2016)
Safe Sites System (now part of the Page Experience System)
These ranking systems are used in various process steps of the Google search.
Deep learning models and other components for ranking
According to statements by Google's Pandu Nayak in the 2023/2024 antitrust proceedings, Google uses the following deep learning models and components for ranking.
What is Rankbrain?
Google RankBrain is an artificial intelligence algorithm netherlands cell phone number list that is part of Google's search engine algorithm and was introduced in late 2015. Its main task is to better understand search queries and improve search results, especially for new, unique or complex queries that Google did not previously know about.
RankBrain uses machine learning to identify patterns in search queries and understand the meaning behind words. It aims to interpret the intent behind a search query to deliver more relevant search results, even when the exact words of the query are not present on the web pages. This makes RankBrain particularly effective at handling vague or ambiguous search queries.
An interesting feature of RankBrain is its ability to self-improve. It continuously learns from search queries and user click behavior to refine its algorithms and increase the accuracy of search results.
Rankbrain is only applied to the first 20-30 documents and adjusts the initial scores of that content. Since Rankbrain is very expensive, it is only used to pre-select documents with the highest initial scores.