Google used in 2015 RankBrain machine learning system to process 15% of searches. Now, whether it is used consistently and this algorithm is changing the classification of a large number of queries.
The search giant relies on machine learning to improve search RankBrain users. Currently, of all the factors that Google uses when calculating the position of each web, this is in third place -by behind and links- content and is used in all the actual queries, so its importance is once more noticeable. Ultimately, the complex operation focuses on rewarding quality of information.
I attending the background of Google algorithms and in 2012 saw the light Knowledge Graph, whose purpose was the improvement and development of semantic search. The update of the same wine in 2013 with the Hummingbird algorithm, which began to relate the search terms in semantic context, approaching human understanding of the language in which queries were drafted.
So with Hummingbird algorithm Google began using the technique of disambiguation, achieving identify the direction with which users used a polysemous word. Thus, the company has directed its steps and efforts to understand user intent and refine results for these more specific with respect to searching. Now, the use of RankBrain aims to integrate machine learning and artificial intelligence with semantic search.
How the algorithm works RankBrain?
Google wants you to find easily and simply, the first way, what you’re looking. To this end, company engineers have implemented RankBrain, whose basic function is to improve Hummingbird transforming words into vectors understood by machines, offering therefore optimum results to the user queries. These elements serve to generate mathematical meanings around related terms, identifying common patterns that relate them.
The problems that Google intends to solve is misunderstanding certain queries, either by considering different or wrong meanings depending on their position in the sentence, the context in which the search or plurals and misspellings is made. Thus, RankBrain has their own self – learning system, detecting the results are not successful to a query based on factors like bounce rate.
The algorithm, in addition to errors, taking into account the high permanence and user interaction on the web page you have accessed from the SERPs. Thus, the algorithm RankBrain continually learns, gradually improving the quality search results based on user behavior.