{"id":11837,"date":"2019-11-28T10:59:11","date_gmt":"2019-11-28T09:59:11","guid":{"rendered":"https:\/\/wordlift.io\/blog\/en\/?post_type=entity&p=11837"},"modified":"2021-11-03T18:00:13","modified_gmt":"2021-11-03T17:00:13","slug":"bert","status":"publish","type":"entity","link":"https:\/\/wordlift.io\/blog\/en\/entity\/bert\/","title":{"rendered":"BERT"},"content":{"rendered":"

The Bidirectional Encoder Representations from Transformers (BERT) is an AI<\/a> developed by Google<\/a> as a means to help machines understand language in a manner more similar to how humans understand language. Specifically, it\u2019s pre-trained, unsupervised natural language processing<\/a> (NLP) model that seeks to understand the nuances and context of human language.<\/span><\/p>\n

It was released as an open-source<\/a> program by Google in 2018 but had an official launch in November 2019. It is now being used in Google searches in all languages, globally and impacts featured snippets.<\/span><\/p>\n

What is BERT used for?<\/span><\/h2>\n

BERT is primarily used to provide better query results by using its understanding of language nuance to deliver more useful results. This goes not only for standard snippets, but for featured snippets as well. It\u2019s said that it will impact at least 1 out of every 10 search results going forward.<\/span><\/p>\n

When BERT uses its understanding of nuance in language, it can understand a user\u2019s intentions through connecting words, such as: and, but, to, from, with, etc. So rather than utilizing only keywords, BERT can understand a user\u2019s query request by examining words like \u201cand\u201d or \u201cverses\u201d in delivering SERP results.<\/span><\/p>\n

\"Example
An example of how BERT uses NLP to distinguish a user’s search intent.<\/figcaption><\/figure>\n

In an example provided by Google, if you search for \u201cparking on a hill with no curb,\u201d you would get SERP<\/a> results and a featured snippet detailing what you need to do if you\u2019re parking a vehicle on a hill where there is no curb. Thanks to BERT\u2019s NLP, Google knows that the word \u201cno\u201d means that there is no curb, whereas previously, if you searched for the same query, you would\u2019ve received results on parking on a hill WITH a curb because your query included the keyword \u201ccurb\u201d but Google didn\u2019t understand the significance of the word no.<\/span><\/p>\n

What is BERTSUM?<\/span><\/h2>\n

BERTSUM is a variant of BERT that is used for extractive summarization of content. Essentially, BERTSUM can be used to extract summaries of web pages and content for several different web pages and sites. This has been known to be particularly useful when writing meta descriptions for hundreds or even thousands of webpages on a site, rather than having to write each one individually.<\/span><\/p>\n

BERT\u2019s effect on RankBrain<\/span><\/h2>\n

RankBrain, being Google\u2019s first AI used to understand queries, has been used to understand queries and content since 2015. While it shares some things in common with BERT, they do not perform the same functions and BERT has not replaced RankBrain<\/a>. RankBrain can do things like, understand what a user is looking for even if they misspelled it or used incorrect grammar whereas BERT seeks to understand the nuances of the language used in a search query.<\/span><\/p>\n

Therefore, while they both share a lot in common and both perform NLP functions for the Google SERP, they are not the same.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

The Bidirectional Encoder Representations from Transformers (BERT) is an AI developed by Google as a means to help machines understand language in a manner more similar to how humans understand language. Specifically, it\u2019s pre-trained, unsupervised natural language processing (NLP) model that seeks to understand the nuances and context of human language. It was released as … Continued<\/a><\/p>\n","protected":false},"author":47,"featured_media":18552,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"wl_entities_gutenberg":"","_wlpage_enable":"","footnotes":""},"categories":[28],"wl_entity_type":[13],"coauthors":[],"class_list":["post-11837","entity","type-entity","status-publish","has-post-thumbnail","hentry","category-world-summit-ai","wl_entity_type-creative-work"],"acf":[],"yoast_head":"\nBERT - WordLift Blog<\/title>\n<meta name=\"description\" content=\"BERT, the Bidirectional Encoder Representations from Transformers is an NLP developed by Google to understand language nuances in a search query.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/wordlift.io\/blog\/en\/entity\/bert\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"BERT - 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