The current WWW is a powerful tool for research and education, but its utility is hampered by the inability of the user to navigate easily the nefarious sources for the information he requires. The Semantic Web is a vision to solve this problem. It is proposed that a new WWW architecture will support not only Web content, but also associated formal semantics [4]. The idea is that the Web content and accompanying semantics (or metadata) will be accessed by Web agents, allowing these agents to reason about the content and produce intelligent answers to users' queries.
The Semantic Web, in practice, comprises a layered framework: an XML layer for expressing the Web content; a Resource Description Framework (RDF) [8] layer for representing the semantics of the content; an ontology layer for describing the vocabulary of the domain; and a logic layer to enable intelligent reasoning with meaningful data [18].
XML was designed as a simple, flexible way of transporting structured documents across the Web. With XML, "tags" or hidden labels may be created - such as or - that annotate Web pages or sections of text within a page. XML is machine-readable, i.e. programs can read and understand it, but the program developer has to know what the page writer uses each tag for. In other words, XML allows users to add arbitrary structure to their documents but says nothing about what the structures mean [5].
The meaning of document content is expressed with RDF that is simply a data model and format that allows the creation of machine-readable data. It comprises a set of triples, i.e. three Universal Resource Identifiers (URI) that may be used to describe any possible relationship existing between the data subject, object and predicate [7] [16]. Thus, all data stored in the system is easily readable and processable. It is important to note that RDF provides the syntax, but not the actual meaning of the properties we ascribe to the data. For example, it does not define what data properties such as Title or Category or Related-To mean. Properties like these are not standalone; they come in packages called domain vocabularies. A learning object, for example, may include a set of properties such as Course, Sub-Section, Author, Title, Similar-To, Difficulty-Level, Rating, etc. Thus, for every domain there is a need for a specific ontology to describe the vocabularies and to make sure they are compatible.
Ontologies in the context of the Semantic Web are specifications of the conceptualization and corresponding vocabulary used to describe a domain [12].
Nuccitelli, R., Guerra, E. and Fernandes, C. (2010) “Parsing XML Documents in Java using Annotations”. In XML: Aplicações e Tecnologias Associadas, 8, Vila do Conde.
But as web designers and audiences well know, the web is still in great need of improvement. Long load times, inconsistent page rendering, and a myriad of other problems plague the web, creating no end of hassle and frustration. However, an emerging technology, cascading style sheets, could eliminate many of the web's largest problems by replacing the primary language of the web, the Hypertext Markup Language (or HTML).
Ontology contains a set of concepts and relationship between concepts, and can be applied into information retrieval to deal with user queries.
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.
Web IS. The importance of web led the classical information systems to transform in order to integrate with web technologies. This means that a web application can access an organization’s dataset. And as we mentioned above, this integration creates new data issues, like security and accessibility.
...feature detectors will be in a particular partially activated state, which is called a signature. This signature will be matched against all the other unique signatures constructed from the InPhO database, and using the rich partial-match properties of dynamic associative networks, determine which elements of the ontology have the most in common with the Document. This set of elements will further be analyzed to locate the appropriate position of the Document within the hierarchy of philosophy.
Resource Description Framework (RDF), Web Ontology Language, Ontology Interchange Language (OIL), DARPA Markup Language (DAML), DAML+OIL, Simple HTML Ontology Exten...
CYC is a very large, multi-contextual knowledge base and inference engine. The development of CYC was started at the Microelectronics and Computer Technology Corporation(MCC) during the early 1980s and continued at Cycorp, Inc. On January 1, 1995 at Austin, Texas. Doug Lenat, the former head of the CYC Project at MCC and the president of Cycorp at present, has lead the development of the CYC project from the beginning. The goal of the Cyc project is to break the software brittleness bottleneck once and for all by constructing a foundation of basic common sense knowledge system and semantic substratum of terms, rules, and relations that will enable a variety of knowledge-intensive products and services. T...
...eloped under the auspices of the World Wide Consortium (W3C).A certain amount of metadata is already provided for Web site resources using the Hypertext Markup Language (HTML).
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.
This paper is intended to be an introductory tutorial on the Very Large Knowledge Base (VLKB) called CYC. Described herein is the reasoning for the origination of the CYC project, the intended usefulness of the project (application areas), how CYC is being constructed, and a brief introduction to the supporting tools that have been developed to interact with the CYC knowledge base.
Content management system is a procedural system that determines how work flows in any given work environment. With reference to the web environment, content management system may be limited to the creation, control, storage and deployment of individual contents on a given web page. Content management system is differentiated from static pages through a number of ways. Ultimately, whereas content management system should enable a manipulative approach towards the use of the web pages in question, static pages give web users no manipulative option of altering the content of the page. Rather, users act as passive beneficiaries who receive the information on the web pages just as they have been stored. This means that given a number of users receiving information from a single server, all users will at any given time receive the same information. Even though the internet has today come to be a great transformation that depends on the principles of content management system in a dynamic way, Eldridge (2001) notes that the internet used to consist solely of HTML or static web pages, that is, web pages that are not changed before being displayed in a web browser.
Ontologies: show the key element in WSMO, offers common terminology used by other WSMO elements and also describe the semantic properties of relations, concepts and set of axioms.
These approaches also have some limitations, in part due to differences between web applications and systems developed and operated under more traditional paradigms. Among these differences, we consider three in particular.