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Ontology Engineering

Ontology Engineering. Introduction. First results are about bats and dolphins. Google Scholar search for query Sentiment Analysis. Why?. Web content is currently formatted for human readers rather than programs

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Ontology Engineering

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  1. Ontology Engineering Introduction

  2. First results are about bats and dolphins

  3. Google Scholar search for query Sentiment Analysis

  4. Why? • Web content is currently formatted for human readers rather than programs • HTML is the predominant language in which Web pages are written (directly or using tools) • Vocabulary describes presentation

  5. HTML? <HTML><BODY> <H2 align=center>Nonmonotonic Reasoning: Context- Dependent Reasoning</H2> <P align=center> <I>by<B>V. Marek</B> and <B>M Truszczynski</B></I> <BR>Springer 1993 <BR>ISBN 0387976892 </P> </BODY></HTML>

  6. HTML? • Inability to cover any content aspects – HTML only describes the appearances of documents and cannot cover any content related aspects. It is therefore unsuitable for explicit queries. • Inability for semantic markup– Individual elements on a page cannot be marked semantically.

  7. Why does this happen?? • The Web content is not machine-accessible • lack of semantics • Not in a proper structure • Not in a machine understandable manner • keyword-based search engines • (e.g. Google, AltaVista, Yahoo)

  8. How to overcome these limitations • Currents situation can be improved by adopting following two strategies • Use the content as it is represented today, and to develop techniques based on artificial intelligence and computational linguistics. • This approach has been followed for sometime now, but despite advances that have been made the task still appears too ambitious. • Represent Web content in a form that is more easily machine processable • Then use intelligent techniques to take advantage of these representations (Semantic Web).

  9. A Layered Approach

  10. XML

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