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The World Wide Web changed the way we live our lives, most notably in the ways we now share, consume and find information. There are many more webpages now than there are people, and links connect these webpages to each other in a giant network that is accessible from your favorite browser.
A downside of this success is that now there’s too much information, so much in fact, that we need machines to intelligently read these webpages and answer our questions. The Semantic Web is a movement and research community that brings together experts from different areas, examples being natural language processing, ontologies, databases, social media, networks and logic, to realize the vision of making the Web machine-readable.
Why is this such a difficult problem? The main reason is that much of the Web, even today, is in a natural language like English or French. These languages are very ambiguous, but we humans have a knack for understanding them due to a variety of factors, not the least of which is our immense store of background knowledge and common sense. Machines are not yet capable of understanding English at the same level as an adult human being, though impressive progress is being made.
To overcome this problem, the Semantic Web presents a vision of the Web as an interlinked network of concepts, relationships and entities, rather than an interlinked network of ‘natural’ webpages. Intelligent systems, often called ‘agents’, can consume the Semantic Web and answer complex questions that now require human labor. The research in the Semantic Web also helps search; e.g. the Google Knowledge Graph, which uses Semantic Web technology, can help you to answer some of your questions without even clicking on a link!