Semantic Web Technologies

1. Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA

2. Lecture Outline • Semantic Web at present • Semantic Web goals. • Semantic Web technologies • Explicit Metadata • Ontologies • Logics • Agents Quratulain

3. Semantic Web • To date Web has developed most rapidly as a medium of documents for people rather than data and information that can be processed automatically. • The Semantic Web aims to provide data that is machine processable. • The Semantic web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Quratulain

4. Semantic Web: At present • Researchers claim that the challenge is in engineering and technology adoption rather than a scientific one. • At present, greatest needs are in the areas of integration, standardization, development of tools, and adoption by users. • Further progress is still required. Quratulain

5. Semantic Web Goals • Building models: quest for describing the world in abstract terms to allow for an easier understanding of complex reality. • Computing with knowledge: constructing reasoning machines that can draw meaningful conclusions from encoded knowledge. • Exchanging information: the transmission of complex information resources among computers that allows us to distribute, interlink, and reconcile knowledge on a global scale.

6. Model Building • Model: simplified description of certain aspects of reality, use for understanding, structuring, or predicting parts of the real world. • Plato (Greek philosopher) proposed answer to following questions. • What is reality? • Which things can be said to exist? • What is the true nature of things? • And lead to a first major contribution in philosophical field now known as ontology.

7. Building Model • Taxonomy: Hierarchical classification • e.g Classification of diseases • Non-hierarchical classification • e.g Thesaurus (relationships such as synonyms and antonyms are not hierarchical)

8. Calculating with knowledge • Domain-independent rules provide template-like ways for inferring knowledge All A are B. All B are C. inferred knowledge that All A are C.

9. Calculating with knowledge • Goal of AI: build machines exhibiting human intelligence • Amount of knowledge for basic AI applications is overwhelming. Transforming human knowledge to machine-processable form is difficult • Inference techniques became too slow for medium or large-scale tasks • Consequently: research focused on restricted domains • Expert systems, rule-based systems for highly structured areas

10. Exchanging information • Applications • E-mail • Online classified • Wikis, blogs, social networks, tagging Quratulain

11. Semantic Web Technologies Following are necessary to achieve Semantic Web goals: • Explicit Metadata • Ontologies • Logic • Agents Quratulain

12. Explicit Metadata • Keyword based system identify the words • An Intelligent agent might able to identify personnel of center. But it will have difficulty in distinguishing manager from secretary. • The semantic Web approach is not the development of super-intelligent agents. Instead the purpose is to add information about content. • The metadata capture part of the meaning of data, thus the term semantic in semantic web. Quratulain

13. Add Metadata HTML: <H1>IBA FCS program</H1><UL> <L1> Instructor: Quratulain<LI> Course: Semantic Web </UL> XML: <FCS-Courses><title>IBA FCS program </title><instructor>Quratulain</instructor><Course>Semantic Web</Course></FCS-Courses> Quratulain

14. Ontologies • Most cited definition by T. R. Gruber: “An ontology is an explicit and formal specification of a conceptualization.” • An ontology describes the domain of discourse includes terms and relationships between terms. • In the context of web, ontologies provides shared understanding of a domain. • Shared understanding overcome the difference in terminology. Quratulain

15. Hierarchy Quratulain

16. Ontology and Web Search • Ontologies are useful for improving the accuracy of Web searches. • The search engines can refer to a precise concept in an ontology instead of collecting all pages. • If query fail to find any relevant documents, the search engine may suggest to the user a more general query. • Ontology languages for the Web are XML, RDF, RDFS, OWL. Quratulain

17. Logic • Logic offers: • Formal language for expressing knowledge. • Well-understood formal semantics. • Automated reasoners can deduce (infer) conclusions from the given knowledge, thus making implicit knowledge explicit. • For logic to be useful on Web • It must be usable in conjunction with other data. • It must be machine processable. Quratulain

18. Logic and Agent • Advantage of logic is • Provide explanations for conclusions by retracing series of inference steps. • Explanation are important for the semantic Web because they increase user’s confidence in Semantic Web agents. • Explanation will also be necessary for activities between agents. Quratulain

19. Agents • Agents are pieces of software that work autonomously. • A personal agent on Web will receive some tasks and preferences, select certain choices, and give answer to the user. • Not replace human users but provide choices. • Agents uses all the technologies: metadata, ontologies, and logic. Quratulain

20. Reading Assignment • http://axel.deri.ie/publications/poll-2010aics.pdf Quratulain