A Web made up of mass of data with no clear means of categorization is almost useless. Think of a library where all of the books have the same dust jacket and are all stacked in one big pile. It's a lot easier to find what you need when those books have recognizable covers and are put into useful groups. Machines in the semantic Web enable better sorting and categorization based on understanding the items they're reading.
Semantics refers to studying meaning in words and symbols. The semantic Web is based on understanding the information contained on Web pages online. The data is summarized in content called metadata. So, the semantic Web is often called a "Web of data." The advantages of the semantic Web depend on the fact that data isn't just stored, it's understood. The pure semantic Web doesn't yet exist at the time of publication.
While Web search engines get "smarter" all the time, in 2011 most major search engines rely on a set of signals to determine the relevance of a page to the query searched. Some of these signals involve semantics. A search engine of the pure semantic Web would be able to understand meaning by looking at layers of metadata about any page, item or thing with information on the Web. In essence, this should make search more specific and less based on comparing and refining results until you find what you need. So, the semantic Web is easier to use.
Web of Things
The Web in mid 2011 is mainly a Web of documents. That means that it exists to share information, mainly in page form. However, the semantic Web moves beyond documents and starts to understand how the things and ideas behind the documents relate to each other. While this sounds a little theoretical and hard to envision, it basically means that your Web browser makes useful connections for you. For example, if you're reading a document about traveling to Mexico for New Years Eve your browser would understand the page content and perhaps suggest exact locations, plane tickets and even show friends considering similar trips.
A simple and early advantage of the semantic Web lies in tagging. Bloggers, for example, usually tag their posts with a few key relevant words about the document. This in turn helps others to find and sort through similar posts. For example, clicking a tag marked "pictures of mountains" brings up a whole range of mountain shots in a photo sharing site. (See Ref 3) This human input of tagging helps a machine to understand what exactly a piece of content is and serve up the right information.
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