By Liyang Yu
The Semantic internet represents a imaginative and prescient for a way to make the large quantity of data on the net immediately processable through machines on a wide scale. For this objective, a complete suite of criteria, applied sciences and comparable instruments were specific and constructed during the last couple of years and so they have now develop into the root for varied new applications.
A Developer’s consultant to the Semantic Web is helping the reader to benefit the middle criteria, key elements and underlying strategies. It offers in-depth assurance of either the what-is and how-to elements of the Semantic internet. From Yu’s presentation, the reader will receive not just a fantastic figuring out concerning the Semantic net, but additionally the right way to mix every little thing to construct new purposes at the Semantic Web.
The moment variation of this publication not just provides particular insurance of the most recent W3C criteria similar to SPARQL 1.1 and RDB2RDF, it additionally updates the readers via following contemporary advancements. extra particularly, it comprises 5 new chapters on schema.org and semantic markup, on Semantic net applied sciences utilized in social networks and on new functions and tasks resembling data.gov and Wikidata and it additionally presents a whole coding instance of creating a seek engine that helps wealthy Snippets.
Software builders in and scholars focusing on net improvement or Semantic internet applied sciences will locate during this e-book the main whole consultant to this fascinating box on hand this present day. in accordance with the step by step presentation of real-world tasks, the place the applied sciences and criteria are utilized, they're going to collect the data had to layout and enforce state of the art applications.
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Extra resources for A Developer’s Guide to the Semantic Web
1 Requirements in Sect. 2 mapped to Semantic Web technologies and standards Requirements Each statement collected by our agent represents a piece of knowledge. Therefore, there has to be a way (a model) to represent knowledge on the Web site. And furthermore, this model of representing knowledge has to be easily and readily processed (understood) by machines This model has to be accepted as a standard by all the Web sites; therefore, statements contained in different Web sites all looked “similar” to each other There has to be a way to create these statements on each Web site, for example, they can be either manually added or automatically generated The statements contained in different Web sites cannot be too arbitrary.
The reason, again, as you can guess, is that although all the services needed to be integrated do exist on the Web, the Web is not programmed to understand and remember the meanings of any of these services. As far as the Web is concerned, all these components are created equal, and there is no way for us to teach our computers to understand the meaning of each component, at least on the current Web. What about the last activity, namely, Web data mining? The truth is, Web data mining applications are not scalable, and they have to be implemented at a very high price, if they can be implemented at all.
And once this is done, for our agent, Figs. 2 are already “glued” together by overlapping the ns0:_x node with the ns1:book-1584889330 node. This gluing process is exactly the data integration process on the Web. Now, without going into the details, it is not difficult to convince ourselves that our agent can answer lots of questions that we might have. com? This is indeed very encouraging. And this is not all. com. Similarly, if LinkedIn were still the LinkedIn of today, our agent could not do much.