The emergence of the World Wide Web (WWW) has brought exciting new possibilities in information access and electronic business. The WWW has grown to be the largest distributed repository of information ever created. Current estimates reveal that the Web currently contains about 3 billion static documents and being accessed by over 500 million users from around the world [6]. Web content consists largely of distributed hypertext and hypermedia, accessible via keyword-based search and link navigation. Simplicity is one of the Web’s major strengths and an important feature in its popularity and growth. It is this simplicity that has fuelled its wide uptake and exponential growth. However, it is this very simplicity that is hampering further growth and exploitation of the Web. The explosion in the range and quantity of Web content also exposes serious shortcomings in the hypertext paradigm [1]. It is increasingly difficult to locate required content through existing search and browse methods ([1], [2], [3]). Finding the right piece of information is often challenging. Search engines can assist in finding material containing specific words, but it is very easy to get lost in the huge amounts of irrelevant material. Selecting the relevant material out of the million web pages on the computer screen becomes a nightmare and manually unachievable as this requires users to read through a large number of retrieved documents to extract the right information. Currently it has been hypothesized that the solution to this problem lies in the ‘invention’ of the machine-understandable semantics for some or all of the information on the WWW. The realization of such a Semantic Web [4] requires developing techniques for expressing machine-understan...
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In 1998, when Google created its search engine, very little data was available about search engines. One of the first search engines was the Wold Wide Web Worm, which was not released unitl 1994. In order to research and create a more dynamic search engine Google’s creators had very little information to go on, and encountered many challenges. It is a challenge to create a high quality search engine as search engines need to crawl and then index millions of pages of information on the web. An additional feature of Google’s large scale search engine is that it will use hypertext information to refine search results. The challenge is to be able to scale the vast amount of data available on the web. The main goal is to improve the quality of search results. The second goal is to be able to make all the data on the web available for academic research. One of the key features of Google that sets it apart from other web search engines is that it is built to scale well to large data sets. It plans to leverage the increase in technological advances and decrease in hardware and storage costs to create its robust system.
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The Internet has encyclopedic capabilities that surpass any previous knowledge collecting endeavors. The pages that we move through seem almost infinite, offering different perspectives and intersecting accounts. These qualities lend a feeling of omniscience to the surfer. “The limitless expanse of gigabytes presents itself to the storyteller as a vast tabula rasa crying out to be filled with all the matter of life” (84). Filling this “limitless expanse” is not without complication. “The reality is much more chaotic and fragmented: networked information is often incomplete or misleading, search routines are often unbearably cumbersome and frustrating, and the information we desire often seems to be tantalizingly out of reach” (84).
In 1990 the World Wide Web was invented, creating a new and never before seen information outlet. Along with the creation of the World Wide Web came the simple to use, never ending access to information. This created a new way for educators and students to achieve information. Now students, instead of researching through books and news articles, and reading the entirety of the literary work, students are able to use a computer, and type in the keywords for the subject they wished to know about.
RDF stands for Resource description framework. We can define RDF as “RDF is a model/standard with the help of which we can define resources on the web”. The common people don’t understand RDF. It is developed to understand and read by computer.RDF is a base for managing metadata. With the help of RDF, we can exchange information between applications, operating systems, and computers on the internet. We can define any information of different web pages with the help of RDF.
Web 2.0 was previously used as a synonym for Semantic Web, but while the two are similar, they do not share precisely the same meaning (Web 2.0).”
M. Rosemann, P. Green, M. Indulska et al., “Using ontology for the representational analysis of process modeling techniques,” International Journal of Business Process Integration and Management, vol. 4, no. 2, 2009.
Our current and future work is oriented to further harness our ontologies with the help of professional telecommunication engineers and domain experts. We are conscious of the challenges ahead that semantic web services could confront particularly during execution in a broad-based industrial applications and hence working on to lessen them. Moreover, we are focusing to figure out further drawbacks and challenges of the semantic web services. More efforts are being made to make the semantic web service in perfect resonance with the modern needs and challenges in order to make it highly dynamic intelligent business application.
The unpredictable increase and growth of information on the World Wide Web, with the progress of innovative electronic devices, has made information of Web increasingly important in everyone’s life. In today’s era, as we
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