RankBrain is a

machine learning Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task ( ...

-based

search engine A search engine is a software system that provides hyperlinks to web pages, and other relevant information on World Wide Web, the Web in response to a user's web query, query. The user enters a query in a web browser or a mobile app, and the sea ...

algorithm, the use of which was confirmed by

Google Google LLC (, ) is an American multinational corporation and technology company focusing on online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, consumer electronics, and artificial ...

on 26 October 2015. It helps Google to process search results and provide more relevant search results for users. In a 2015 interview, Google commented that RankBrain was the third most important factor in the ranking algorithm, after links and content, out of about 200 ranking factors whose exact functions are not fully disclosed. , "RankBrain was used for less than 15% of queries." The results show that RankBrain guesses what the other parts of the Google search algorithm will pick as the top result 80% of the time, compared to 70% for human search engineers. If RankBrain sees a word or phrase it is not familiar with, the program can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries or keywords. Search queries are sorted into word vectors, also known as “distributed representations,” which are close to each other in terms of linguistic similarity. RankBrain attempts to map this query into words (entities) or clusters of words that have the best chance of matching it. Therefore, RankBrain attempts to guess what people mean and records the results, which adapts the results to provide better user satisfaction. RankBrain is trained offline with batches of past searches. Studies showed how RankBrain better interpreted the relationships between words. This can include the use of

stop word Stop words are the words in a stop list (or ''stoplist'' or ''negative dictionary'') which are filtered out ("stopped") before or after processing of natural language data (i.e. text) because they are deemed to have little semantic value or are ot ...

s in a search query ("the," "and," "without," etc.) words that were historically ignored previously by Google, but are sometimes of a major importance to fully understanding the meaning or

intent An intention is a mental state in which a person commits themselves to a course of action. Having the plan to visit the zoo tomorrow is an example of an intention. The action plan is the ''content'' of the intention while the commitment is the '' ...

behind a person’s search query. It is also able to parse patterns between searches that are seemingly unconnected, to understand how those searches are similar to each other. Once RankBrain's results are verified by

's team, the system is updated and goes live again. Google has stated that it uses tensor processing unit (TPU) ASICs for processing RankBrain requests.

Impact on digital marketing

RankBrain has allowed Google to speed up the algorithmic testing it does for keyword categories to attempt to choose the best content for any particular keyword search. This means that old methods of gaming the rankings with false signals are becoming less and less effective, and the highest quality content from a human perspective is being ranked higher in Google. RankBrain has helped

Google Hummingbird Hummingbird is the codename given to a significant algorithm change in Google Search in 2013. Its name was derived from the speed and accuracy of the hummingbird. The change was announced on September 26, 2013, having already been in use for a mo ...

(the 2013 version of the ranking algorithm) provide more accurate results because it can learn words and phrases it may not know. It also learns them specifically for the country, as well as language, in which a query is made. So, if one looks up a query with the word ''boot'' in it within the United States, one will get information on footwear. However, if the query comes through the UK, then the information could also be in regard to storage spaces in cars.

References

{{Google LLC Google Search Search engine optimizationbr>角鋼BloggerBoosted