RankBrain

Last updated

RankBrain is a machine learning-based search engine algorithm, the use of which was confirmed by Google on 26 October 2015. [1] It helps Google to process search results and provide more relevant search results for users. [2] In a 2015 interview, Google commented that RankBrain was the third most important factor in the ranking algorithm, after with links and content, [2] [3] out of about 200 ranking factors. [4] whose exact functions in the Google algorithm are not fully disclosed. As of 2015, "RankBrain was used for less than 15% of queries." [5] 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. [2]

If RankBrain sees a word or phrase it isn’t 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. [6]

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 words 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 behind a person’s search query. It’s also able to parse patterns between searches that are seemingly unconnected, to understand how those searches are similar to each other. [7] Once RankBrain's results are verified by Google's team, the system is updated and goes live again. [8]

Google has stated that it uses tensor processing unit (TPU) ASICs for processing RankBrain requests. [9]

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. [10] [ unreliable source? ]

RankBrain has helped Google Hummingbird (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. [11] [ unreliable source? ]

Related Research Articles

<span class="mw-page-title-main">Google Search</span> Search engine from Google

Google Search is a search engine operated by Google. It allows users to search for information on the Web by entering keywords or phrases. Google Search uses algorithms to analyze and rank websites based on their relevance to the search query. It is the most popular search engine worldwide.

Meta elements are tags used in HTML and XHTML documents to provide structured metadata about a Web page. They are part of a web page's head section. Multiple Meta elements with different attributes can be used on the same page. Meta elements can be used to specify page description, keywords and any other metadata not provided through the other head elements and attributes.

Spamdexing is the deliberate manipulation of search engine indexes. It involves a number of methods, such as link building and repeating related and/or unrelated phrases, to manipulate the relevance or prominence of resources indexed in a manner inconsistent with the purpose of the indexing system.

Search engine optimization (SEO) is the process of improving the quality and quantity of website traffic to a website or a web page from search engines. SEO targets unpaid traffic rather than direct traffic or paid traffic. Unpaid traffic may originate from different kinds of searches, including image search, video search, academic search, news search, and industry-specific vertical search engines.

<span class="mw-page-title-main">Metasearch engine</span> Online information retrieval tool

A metasearch engine is an online information retrieval tool that uses the data of a web search engine to produce its own results. Metasearch engines take input from a user and immediately query search engines for results. Sufficient data is gathered, ranked, and presented to the users.

The anchor text, link label, or link text is the visible, clickable text in an HTML hyperlink. The term "anchor" was used in older versions of the HTML specification for what is currently referred to as the "a element", or <a>. The HTML specification does not have a specific term for anchor text, but refers to it as "text that the a element wraps around". In XML terms, the anchor text is the content of the element, provided that the content is text.

In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases.

In text processing, a proximity search looks for documents where two or more separately matching term occurrences are within a specified distance, where distance is the number of intermediate words or characters. In addition to proximity, some implementations may also impose a constraint on the word order, in that the order in the searched text must be identical to the order of the search query. Proximity searching goes beyond the simple matching of words by adding the constraint of proximity and is generally regarded as a form of advanced search.

Scott Craig Deerwester is a patented and highly cited computer scientist who created the mathematical and natural language processing technique (NLP) known as latent semantic analysis (LSA),. His expertise includes a range of technologies important to addressing today's societal challenges including information and data science, software systems architecture, and data modeling.

A video search engine is a web-based search engine which crawls the web for video content. Some video search engines parse externally hosted content while others allow content to be uploaded and hosted on their own servers. Some engines also allow users to search by video format type and by length of the clip. The video search results are usually accompanied by a thumbnail view of the video.

Local search is the use of specialized Internet search engines that allow users to submit geographically constrained searches against a structured database of local business listings. Typical local search queries include not only information about "what" the site visitor is searching for but also "where" information, such as a street address, city name, postal code, or geographic coordinates like latitude and longitude. Examples of local searches include "Hong Kong hotels", "Manhattan restaurants", and "Dublin car rental". Local searches exhibit explicit or implicit local intent. A search that includes a location modifier, such as "Bellevue, WA" or "14th arrondissement", is an explicit local search. A search that references a product or service that is typically consumed locally, such as "restaurant" or "nail salon", is an implicit local search.

<span class="mw-page-title-main">Search engine</span> Software system for finding relevant information on the Web

A search engine is a software system that provides hyperlinks to web pages and other relevant information on the Web in response to a user's query. The user inputs a query within a web browser or a mobile app, and the search results are often a list of hyperlinks, accompanied by textual summaries and images. Users also have the option of limiting the search to a specific type of results, such as images, videos, or news.

A search engine results page (SERP) is a webpage that is displayed by a search engine in response to a query by a user. The main component of a SERP is the listing of results that are returned by the search engine in response to a keyword query.

Search engine indexing is the collecting, parsing, and storing of data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, and computer science. An alternate name for the process, in the context of search engines designed to find web pages on the Internet, is web indexing.

Keyword research is a practice search engine optimization (SEO) professionals use to find and analyze search terms that users enter into search engines when looking for products, services, or general information. Keywords are related to search queries.

Natural-language user interface is a type of computer human interface where linguistic phenomena such as verbs, phrases and clauses act as UI controls for creating, selecting and modifying data in software applications.

<span class="mw-page-title-main">PageRank</span> Algorithm used by Google Search to rank web pages

PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term "web page" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According to Google:

PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites.

Google Penguin is a codename for a Google algorithm update that was first announced on April 24, 2012. The update was aimed at decreasing search engine rankings of websites that violate Google's Webmaster Guidelines by using now declared Grey Hat SEM techniques involved in increasing artificially the ranking of a webpage by manipulating the number of links pointing to the page. Such tactics are commonly described as link schemes. According to Google's John Mueller, as of 2013, Google announced all updates to the Penguin filter to the public.

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 month. "Hummingbird" places greater emphasis on natural language queries, considering context and meaning over individual keywords. It also looks deeper at content on individual pages of a website, with improved ability to lead users directly to the most appropriate page rather than just a website's homepage.

Local search engine optimization is similar to (national) SEO in that it is also a process affecting the visibility of a website or a web page in a web search engine's unpaid results often referred to as "natural", "organic", or "earned" results. In general, the higher ranked on the search results page and more frequently a site appears in the search results list, the more visitors it will receive from the search engine's users; these visitors can then be converted into customers. Local SEO, however, differs in that it is focused on optimizing a business's online presence so that its web pages will be displayed by search engines when users enter local searches for its products or services. Ranking for local search involves a similar process to general SEO but includes some specific elements to rank a business for local search.

References

  1. ↑ "Google: RankBrain Archives". Search Engine Land. Retrieved 2020-11-03.
  2. 1 2 3 Clark, Jack. "Google Turning Its Lucrative Web Search Over to AI Machines". Bloomberg Business. Bloomberg. Retrieved 28 October 2016.
  3. ↑ "Now we know: Here are Google's top 3 search ranking factors". Search Engine Land. 2016-03-24. Retrieved 2017-04-14.
  4. ↑ "Google's 200 Ranking Factors: The Complete List (2022)". Backlinko. 2013-04-18. Retrieved 2022-02-23.
  5. ↑ "Google uses RankBrain for every search, impacts rankings of "lots" of them". Search Engine Land. 2016-06-23. Retrieved 2017-04-14.
  6. ↑ Capala, Matthew (2016-09-02). "Machine learning just got more human with Google's RankBrain". The Next Web. Retrieved 2017-01-19.
  7. ↑ "The real impact of Google's RankBrain on search traffic". The Next Web. Retrieved 2017-05-22.
  8. ↑ Sullivan, Danny. "FAQ: All About The New Google RankBrain Algorithm". Search Engine Land. Retrieved 28 October 2015.
  9. ↑ "Google's Tensor Processing Unit could advance Moore's Law 7 years into the future". PCWorld. Retrieved 2017-01-19.
  10. ↑ "NonTechie RankBrain Guide [Infographic]". www.logicbasedmarketing.com. Retrieved 2018-02-16.
  11. ↑ "The Google RankBrain Algorithm Explained - Best for SEO". www.seonewsagency.com. Retrieved 2018-11-13.

角鋼

This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.