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DETAILS ABOUT http://data.wordlift.io/wl0216/entity/semantic_web

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dct:relation http://data.wordlift.io/wl0216/entity/world_wide_web_consortium
dct:relation http://data.wordlift.io/wl0216/entity/world_wide_web
dct:relation http://data.wordlift.io/wl0216/entity/tim_berners-lee
dct:relation http://data.wordlift.io/wl0216/entity/google
dct:relation http://data.wordlift.io/wl0216/entity/hummingbird
dct:relation http://data.wordlift.io/wl0216/entity/artificial_intelligence
dct:title "Semantic Web"@en^^rdf:langString
dct:title "semantic web"@en^^rdf:langString
schema:alternateName "semantic web"@en^^rdf:langString
schema:description "The Semantic Web is a collaborative movement led by the international standards body, the World Wide Web Consortium (W3C). The standard promotes common data formats on the World Wide Web. By encouraging the inclusion of semantic content in web pages, the Semantic Web aims at converting the current web dominated by unstructured and semi-structured documents into a "web of data" — that it can be read directly by the computers. The Semantic Web stack builds on the W3C's Resource Description Framework (RDF). To get a quick introduction to the Semantic Web, have a look at this short video by Gennaro Cuofano: https://youtu.be/MqSBBaBNmt0 Why the Semantic Web? A few steps back February 2009, Long Beach, CA, Sir Tim Berners-Lee, the founding father of the web is on a TED stage asking for help from the audience. In fact, he is envisioning the formation of a new web, built over the past net. A Semantic Web based on open linked data. Now the Semantic Web is here, and its technologies are available to digital marketers to make their SEO strategy more effective. How did we get there? On august 1991 the first website went live. Today well over a billion websites comprise the web. http://t.co/D9pwMXuZOa recently passed a billion websites by their count... — Tim Berners-Lee (@timberners_lee) September 16, 2014 In less than a decade the number of websites exploded. It comprised millions of pages. Sir Tim Berners-Lee figured out he could connect web pages with what we all know today as hypertext. However, surfing the web was still limited because you could just go from one page to the next through links: the effort it took to find what you were looking for was massive. That is why many ventured out in finding a way to search through those pages to find specific content to queries. On that premise, at the end of the 90s search engines, like Google, sprouted up. In fact, PageRank was the foundation of Google, an algorithm that could rank pages on the web based on the popularity of each page. The more quality backlinks a website received the more it could rank higher in the SERP. Backlinks are still the backbone of the web. However on that backbone a new web blossomed. Back in 2012, futurist Ray Kurzweil arrived at Google, with one mission: make search engines understand human language. From that quest Google updated its algorithm in 2013, with Hummingbird and later on in 2015, AI became a major factor for search RankBrain. It was a revolution. In fact, even though Google looks at more than 200 factors to assess the ranking of a page, it also uses Artificial Intelligence to rank those pages. In other words, Google looks more and more at the intention behind a user query based on the context rather than keywords. For instance, if I type in the search box "french fries" I may be looking for something to eat or just the story behind the name. Of course, if I do this search at 8 a.m. in the morning most probably I intend to know more about the historical facts. If I do the same search at 8 p.m., I may be looking for something to eat for dinner. But how does the search engine know what is the context? It reads human language, through Natural Language Processing (NLP).  How is WordLift building the Semantic Web? Word Lift is using Schema.org and knowledge graphs to contribute to this web of data. Every document on the Web is about many different kinds of “things” called entities. WordLift adds the schema.org markup to the entities in a text and uses them to describe content. Plus, WordLift publishes these entities and their properties in an intelligent model — technically called “knowledge graph” — designed to help computers understand real-world “things” and their relationships to one another. The graph is published using linked data and it is used, in WordLift, to help semantic search crawlers “think” the way we do and that helps us, in return, find information more efficiently."@en^^rdf:langString
schema:image https://wordlift.io/blog/en/wp-content/uploads/sites/3/2017/03/semantic-publishing-wordlift.png
schema:name "Semantic Web"@en^^rdf:langString
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schema:url https://wordlift.io/blog/en/entity/semantic-web/
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rdfs:label "Semantic Web"@en^^rdf:langString
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