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  1. Semantic Web Dushyant Rajput (05005003) Neelmani Singh (05005019) Pratik Jawanpuria (05005022) Jayant Nagda (05D05001) Nirdesh Chauhan (05D05002)

  2. Motivation • Problem: Web was built for humans • web content today is designed for humans to read, not for computer programs to read and manipulate. • Computers have no reliable way to process the semantics and bring structure to the meaningful content on the web. • Solution: make the Web friendlier for machines • we need “machine-understandable” content (not “machine-readable”, we already have that) • “machine-understandable” means content with accessible formal semantics • Why semantic web? • Extend the current existing paradigm of human computer interaction which will allow machines to analysis data in a much better way which they merely display right now.

  3. The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content. - Wikipedia

  4. Semantic Web Architecture

  5. Semantic Web Agents • Nirdesh Chauhan

  6. World in the reign of Semantic Web My agent interacts with IMDB server agent to find some sci-fi movies with rating > 8.0 Me: I want to see a movie. Give me some suggestions. Me: Can Dr. Bose postpone the appointment to tomorrow morning?? Me: Fine !! Schedule my appointment and also book the tickets for 6 pm show. Agent: Matrix and Krrish are some good options.Matrix is currently running in HumaAdlabs. Shows at 6 pm, 9:30 pm. Me: No, give me some current sci-fi movies !! Me: Ok. Book my tickets for show at 6. Agent: TaareZameen Par and Chak De India are good options. Agent: You have an appointment with Dr. Bose at 6:30. Should I book ?? My agent interacts with Mr. Bose’s agent. Agent: Tomorrow morning 9 am is fine with Dr. Bose. My agent interacts with trusted agents to enquire about some good movies

  7. Semantic Web Agents • An agent is an intermediary who makes a complex organization externally accessible.For example, travel agent. • Semantic Web Agent:Programs that collect Web content from diverse sources, process the information and exchange the results with other agents. • Semantic Web may be viewed as:1. An expert system with a distributed knowledge base.2. A society of agents that solve complex knowledge-based tasks. • Agents are viewed as primary consumers of knowledge. Agents capture the notion of the use of entities to solve complex problems on the Web.

  8. Characteristics of Agents • There is no such standard definition for an agent. However some peculiar characteristics that a Semantic Web Agent must possess are: IntelligenceAutonomyReactivityPro-activenessSocial ability • These definitions are subject to different interpretations.For example, there are many different definitions of what it means for an agent to be truly autonomous. • All that we require is that our agent can interact with other agents, and do useful work for us.

  9. Multi-Agent System • MAS is a system composed of several software agents, collectively capable of reaching goals that are difficult to achieve by an individual agent • MAS are necessarily distributed and concurrent in nature.However, A distributed system prescribes a static pattern of behavior towards a common goal.Whereas an agent system is more dynamic with individual agents acting autonomously towards their own goals. • Agents in a MAS:1. Work autonomously to achieve their own goal.2. Interoperate with other agents as a part of MAS.

  10. Reactive Agents • A purely reactive agent does not perform any kind of deduction. Hence, relatively straightforward to implement and map environment states directly to actions. E.g. Stock price monitoring. • They act as a sensor on the environment and are triggered by specific events. • Engineered to respond to changes in the environment which we represent as input events. A(environment state) → action • Implementation Equation-based approach - for events that occur many times, such as price fluctuations.State-based approach - for events that are largely one-time, such as messages.

  11. Practical Reasoning Agents • The practical reasoning agents based on the BDI model.B(beliefs) - knowledge about the current environment state.D(desires) - state of affairs the agent would like to bring about.I(intentions) - desires that the agent has committed to achieving. • Commitment strategies used to determine the persistence of the intentions: Blind, Single-minded and Open-minded. Reason(B, D, I) Do p ← next percept // Changes in the behaviour triggered by external events B ← revise(B, Ò) // Agents’ beliefs are revised in light of these percepts D ← options(B, I) // No. of possible options arise for action I ← deliberate(B, D, I) // Agent deliberates on competing options P ← plan(B, I, A) // performs a means–ends analysis on the intentions. execute(P) // Once a suitable plan (P) has been formed, we execute while true

  12. Semantic Web: Logic Layer • Neelmani Singh

  13. Semantic Web : Logic Layer • For the Semantic Web, semantic indicates that the meaning of data on the Web that can be discovered—not just by people, but also by computers • But this discovery is not possible without logic. • Computers will need to apply logical reasoning to all kinds of “statements” , and those statements will be distributed across the Web.

  14. Roles of Logic for the SW • Application and evaluation of rules • Inferring facts that haven’t been explicitly stated. • Explaining why a particular conclusion has been reached. • Detecting contradictory statements and claims. • Specifying ontologies and vocabularies of all kinds. • Representing knowledge. • Playing a key role in the statement and execution of queries to obtain information from stores of data on the Semantic Web. • Combining information from distributed sources in a coherent way.

  15. Rules • Specialized kind of rule used , the kind often used by so-called expert systems: IF <logical conditions are met> THEN <perform specified actions> • Evaluating the truth of the logical conditions involves logic, but there is more to it. Rules are often chained together. • The Semantic Web will have several additional needs: • A Web-compatible language for expressing rules • The ability to specify the kinds of rules and their relationships and constraints. • Ways to handle incompatible rules.

  16. Inferring facts and Explanations • The Semantic Web will be a very large, open system. So inferring facts from given facts and rules is essential (Open World model). • The ability to explain a train of reasoning may emerge as one of the most important capabilities a Semantic Web reasoning system can have. • If Pratik is allowed access to Neelmani's bank account, it may become important why the conclusion was reached. • If Mr. Dushyant's mother’s name is “Sunita” then “Sunita” must be a woman.

  17. Contradictions and Interpretations • What will happen if a Semantic Web system encounters a contradiction? • Isn’t trivial because in pure logic, a contradiction would allow anything to be proved. • The obvious thing to do would be to regard each statement as a kind of claim that may or may not be strongly supported. • To provide an alternative, the current version of the RDF specifications define a way to understand the meaning of a collection of RDF statements that can deal with the possibility of contradictory information at the cost of more computing power.

  18. Combining information • Problems can arise from trying to combine information from multiple sources on the Semantic Web. Here are some of the most prominent: • Different sources may use different ontologies (different vocabularies for the same things)‏ • Different sources may have different semantics for the (apparently) same things. • Different sources may contain contradictory information. • Different sources may have different degrees of reliability.

  19. Ontologies • An ontology establishes the things that a system can talk and reason about. This means the vocabulary. • The terms have logical relationships to each other that need to be specified, and this in turn means that any ontology system must adopt some variety of logic. • Ontology supplies the concepts and terms. • logic provides ways to make statements that define and use them, and to reason about collections of statements that use the concepts and terms. • In the Semantic Web, the role of logic will be very different from the role of most other components of the Semantic Web layer cake. But WHY ?? Because it isn’t information to be exchanged.

  20. Semantic Web Components • Dushyant Rajput

  21. Semantic Web Components • Extensible Markup Language(XML) provides an elemental syntax to structure data. • XML schema provides and restricts the structure and content of elements in XML documents. • Resource Description Framework (RDF) is a language for expressing data models in XML syntax. • RDF schema is a vocabulary for describing properties and classes of RDF-based resources. • Web Ontology Language (OWL) provides additional vocabulary for describing properties and relations between classes.

  22. Resource Description Framework The need for RDF :- • Make all data and metadata accessible to computers and addressable over networks. • Provide standard way to refer to any particular bit of information. To achieve these RDF uses a simple data model :- • Resources refers to objects. • Statements links two resources. It encodes information as triples subject – predicate/property - object/value.

  23. RDF (continued ...)‏ • Example: (Person, Name, “Neelmani Singh”)‏ Subject Predicate Object • Resource Identification :- URI (Uniform Resource Identifier) references = URI + fragment identifier(the part that follows the # sign after a URI, if any). Eg:- http://www.w3.org/1999/02/22-rdf-syntax-ns # Statement

  24. RDF Graph representation

  25. Ontology Framework • Resource Description Framework Schema Specification (RDFS) provides semantics for generalized-hierarchies of properties and classes. • Web Ontology Language (OWL) • Uses properties of RDFS along with new ones. • Has W3C recommendations.

  26. Semantic Web Services • Jayant Nagda

  27. Web Services • Web services are a new breed of Web application. They are self-contained, selfdescribing, modular applications that can be published, located, and invoked across the Web. Web services perform functions, which can be anything from simple requests to complicated business processes. • Once a Web service is deployed, other applications (and other Web services) can discover and invoke the deployed service.

  28. Architecture • Web: • URIs: specific addresses of web-elements • HTML: way of describing documents. • HTTP: a protocol that is used to retrieve information on web. • Semantic Web: • UDDI: provides a mechanism of finding web services. • WSDL: defines a service. • SOAP: a message layout specification that defines a uniform way of passing XML-encoded data.

  29. Describing a web service • WSDL (Web Services Description Language) is an XML-based language that provides a model for describing public interface to a Web services. • Services as a collection of ports. Messages are abstract. • A client program connecting to a web service can read the WSDL to determine what functions are available on the server.

  30. Discovering web services • UDDI (Universal Description Discovery and Integration)is a platform-independent, XML-based registry for businesses worldwide to list themselves on the Internet. • UDDI is an open industry initiative, sponsored by OASIS, enabling businesses to publish service listings and discover each other.

  31. SOAP • SOAP (Simple Object Access Protocol) is a protocol for exchanging XML-based messages over computer networks, normally using HTTP. • SOAP uses RPC (Remote Procedure Call)

  32. Semantic Web Trust • Pratik Jawanpuria

  33. Semantic Web Trust • The concept of Semantic Web is great, but who would trust such as system if anyone can say anything • If one person says that x is blue, and another says that x is not blue, doesn't the whole Semantic Web fall apart? • So how to know which is trustworthy and whom to believe? • To confront these situation, we have Semantic Web Trust.

  34. Trust Policies in Day to Day Life • A trust policy is a subjective procedure used for evaluating the trustworthiness of information in a specific situation. • Try Dominos's pizza good but not pasta. • Trust Pratik on science fiction movies but not on political news. • Believe in media only on sports news. • See a movie if its IMDB's rating in above 7. • Trust professors on their research field. • We have to allow similar range of trust policies on the Semantic web

  35. Digital Signature Web of Trust

  36. Policy-based Trust Management • Trust relies on "STRONG SECURITY" mechanisms such as digital signatures and trusted certification authorities. • Seen as a solution of problem of authorization and access control in open systems. Reputation-Based Trust Management • include rating systems like the one used by eBay and Web-Of-Trust mechanisms. • IMDB's movie ratings • Social networks like Orkut, Facebook.

  37. Context-Based Trust Mechanisms • Use meta information about the circumstances in which information has been claimed e.g. who said, what, when and why. • Trust a toothpaste if a dental doctor prescribes it • Include role based trust mechanisms, using the author's role or his membership in the specific group, for trust decisions. • Distrust all members of organization X Content-Based Trust Mechanisms • Use rules and axioms together with the information content itself and related information about the same topic given by other providers • Distrust the cricket news if India makes less than 100 runs. • Distrust product prices that are more than 50% below the average price.

  38. Integrated View of Trust Management • Each of the above mechanism address the problem from a different perspective. • In many cases it will be desirable to combine them to handle situations like : • a seller is interested in protecting an item on sale in different ways depending on the value of the item: based on reputation if the price is few hundreds of rupees (e.g. a T-shirt) or based on policies if it is of thousands (e.g. requiring a digital signature for flight ticket)

  39. Prototype of trust architecture • retrieved information is used within the • application’s context • - provides functionality to browse through • explanations why data should be trusted • handles the actual trust decisions • using query-specific trust policies - stores the aggregate information • handles the aggregation of information • from different sources • add provenance metadata to the • information

  40. Conclusion • Ontologies  Reasoning  Agents  Trust • Knowledge representation is very well developed insemantic web. • We need to • move from tools to autonomous systems that work on our behalf • introduce formal semantics (machine-understandable content) • Semantic web trust and agent communication still remains the least explored of all the layers of semantic web. • Search engines based on ontologies have already come uphttp://swoogle.umbc.edu/

  41. Bibliography • Explorers-guide-to-the-semantic-web (by Thomas B. Passin) • Agency and the Semantic web (by Christopher Walten) • Using Context- and Content-Based Trust Policies on the Semantic Web. WWW2004 : Christian Bizer, Radoslaw Oldakowski. • An Integration of Reputation-Based and Policy-Based Trust Management The Semantic Web and Policy Workshop at ISWC2005 (citeseer.ist.psu.edu/576212.html) • http://www.scientificamerican.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21&catID=2 (by Tim Berners-Lee) • Semantic Web Services (IEEE, 2001), Sheila A. McIlraith, Tran Cao Son, and Honglei Zeng, Stanford University. • Wikipedia (http://www.wikipedia.com) • http://logicerror.com/semanticWeb-long