Google had difficulty interpreting queries that had never been made before, it did not know how to handle unknown search queries, according to statistics about 15% of daily queries on Google have never been searched.
To address this challenge, Google needs an intelligent system capable of guessing the expressions of these queries, identifying what lies job function email list behind these new queries, and attempting to present the most effective solutions to its users.
Google created RankBrain to improve the results it provides to its users and to provide relevant results for queries typed for the first time.
What is Google RankBrain?
Created by Greg Corrado » RankBrain is an artificial intelligence algorithm, a machine learning system that aims to process unknown queries and match them with existing searches in a large database, thus providing users with the most relevant search results.
Understanding Artificial Intelligence and Machine Learning
It is similar to human intelligence. It
is thanks to the set of theories and techniques (mathematical and statistical approaches) that artificial intelligence has allowed computers optimising campaigns based on cost per click (cpc) to become intelligent and to be able to learn and improve automatically based on its past experience, to reason better to solve problems themselves.
Machine learning allows the analysis of huge amounts of data.
How does RankBrain work?
RankBrain therefore uses artificial intelligence to copy enormous quantities of data written into mathematical entities called “vectors”, then make calculations to find relationships between the vectors whose expressions are semantically close.
- The engine searches for all vectors close to the user’s in its base of pre-calculated vectors
- the user receives an enriched result with the words present in the nearby vectors.
Example :
An Internet user types words, this query will be formulated in the form of a vector using the RankBrain algorithm, the latter does the search if it is detected as unknown, it will be compared to the closest vectors in order to establish a new relationship and propose a result which will then be kept for machine learning
With RankBrain, Google uses:
- Mathematical processes: vector sale lead representation of natural language processing “groups of words, sentences, paragraphs and questions,
- A thorough understanding of semantics, with a study of syntax, word analysis, word relationships, semantics, contexts,
In order to offer users relevant results that best match their searches.
The news is that one of your pages may rank for multiple queries, i.e., for quite different keywords with the same intent.
For example, if you type either “Rent a wedding venue in Paris” or “Rent a wedding venue in Paris,”
Google will be able to understand that these two queries have the same intent.