An Introduction of Semantic Web

November 12, 2017 Author: virendra
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The current WWW has a huge amount of data that is often unstructured and usually only human understandable. The Semantic Web aims to address this problem by providing machine interpretable semantics to provide greater machine support for the user. Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in co-operation. The semantic web will provide intelligent access to heterogeneous, distributed information enabling software products to mediate between user needs and the information source available.

Semantic Web Structure

Figure 1: Semantic Web Structure





The Internet contains more than 10 billion static pages of information to be used by more than 1000 million users spread over the world. It is difficult to access & maintain this enormous amount of data using natural languages. It is rather difficult to bridge the gap between the available information and the techniques used for accessing it. The web content is increasing at very faster rate and difficult for search engines to cope up with it despite new techniques of searching. The Semantic Web’s establishes machine understandable Web resources. Researchers in this area plan to accomplish this by creating ontology and logic mechanisms and replacing HTML with markup languages such as XML, RDF, OIL, and DAM.

Semantic Web is




  • Providing a common syntax for machine understandable statements.
  • Establishing common vocabularies.
  • Agreeing on a logical language.
  • Using the language for exchanging proofs.

The Semantic Web has a layer structure that defines the levels of abstraction applied to the Web. At the lowest level is the familiar World Wide Web, then progressing to XML, RDF, Ontology, Logic, Proof and Trust. The main tools that are currently being used in the Semantic Web are ontologies based on OWL (Web Ontology Language) and its associated reasoners. Semantic Web is the advanced technique used by the web to fulfil the client’s requirements. In Semantic Web, lot of information can be stored in RDF in an XML file format. This information can be extracted by the users depending upon their needs. This can be done by accepting the user request and providing response to the user by extracting the information from the RDF. Thus the information can be easily extracted by the Web.




With the propagation of internet, email, instant messaging, audio video conferencing the explosion of information was out of control of searching technologies.

  • Knowledge Management
  • Business-to-customer e-commerce
  • Business- to-Business e-commerce
  • Semantic web agents

The semantic web aims to provide advanced knowledge management systems, which should provide knowledge acquiring, accessing and maintaining in the repositories.

Semantic Web Mining

The human ability for information processing is limited on the one hand, whilst otherwise the amount of available information of the Web increases exponentially, which leads to increasing information saturation. In this context, it becomes more and more important to detect useful patterns in the Web, thus use it as a rich source for data mining .

The research area of Semantic Web Mining is aimed at combining two fast developing fields of research: the Semantic Web and Web Mining. The idea is to improve, on the one hand, the results of Web Mining by exploiting the new semantic structures in the Web; and to make use of Web Mining, on the other hand, for building up the Semantic Web.­ These two fields address the current challenges of the World Wide Web (WWW): turning unstructured data into machine-understandable data using Semantic Web tools. As the Semantic Web enhances the first generation of the WWW with formal semantics, it offers a good basis to enrich Web Mining: The types of (hyper) links are now described explicitly, allowing the knowledge engineer to gain deeper insights in Web structure mining; and the contents of the pages come along with a formal semantics, to apply mining techniques which require more structured input.

References

[1] Semantic Web Mining: State of the art and future directions, Stumme. G, Hotho. A, Berendt B, Web Semantics: Science, Services and Agents on the World Wide Web 4(2) (2006) 124 – 143 Semantic Grid – The Convergence of Technologies.

[2] Hai Zhuge, “China’s E-Science Knowledge Grid Environment”, Chinese Academy of Sciences

[3] Grigoris Antoniou and Frank van Harmelan ,”A Semantic Web Primer” ,The MIT Press, Cambridge Massachusetts, London, England.

[4] Towards Semantic Web Mining, Berendt B, Hotho A, Stumme G (2002). ISWC 2002, First International Semantic Web Conference, Sardinia, Italy, June 9-12, 2002, Springer

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