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Semantic Web Technologies. Lecture # 2 Faculty of Computer Science, IBA. Lecture Outline. Semantic Web at present Semantic Web goals. Semantic Web technologies Explicit Metadata Ontologies Logics Agents. Semantic Web .

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semantic web technologies

Semantic Web Technologies

Lecture # 2

Faculty of Computer Science, IBA

lecture outline
Lecture Outline
  • Semantic Web at present
  • Semantic Web goals.
  • Semantic Web technologies
    • Explicit Metadata
    • Ontologies
    • Logics
    • Agents


semantic web
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.


semantic web at present
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.


semantic web goals
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.
model building
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.
building model
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)
calculating with knowledge
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.

calculating with knowledge1
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
exchanging information
Exchanging information
  • Applications
    • E-mail
    • Online classified
    • Wikis, blogs, social networks, tagging


semantic web technologies1
Semantic Web Technologies

Following are necessary to achieve Semantic Web goals:

  • Explicit Metadata
  • Ontologies
  • Logic
  • Agents


explicit metadata
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.


add metadata
Add Metadata


<H1>IBA FCS program</H1><UL>

<L1> Instructor: Quratulain<LI> Course: Semantic Web



<FCS-Courses><title>IBA FCS program </title><instructor>Quratulain</instructor><Course>Semantic Web</Course></FCS-Courses>


  • 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.




ontology and web search
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.


  • 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.


logic and agent
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.


  • 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.


reading assignment
Reading Assignment