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Enhancing Web Answer Trust Using Knowledge Provenance

Learn how the IWTrust framework aids users in establishing trust in web answers by leveraging Knowledge Provenance. Explore trust computation, social recommender networks, and the importance of proof and justification for trustworthy information.

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Enhancing Web Answer Trust Using Knowledge Provenance

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  1. IWTrust:Improving User Trust in Answers from the Web Ilya Zaihrayeu ITC-IRST Paulo Pinheiro da Silva Deborah L. McGuinness Stanford University

  2. Trusting Answers • It may be challenging for a user to establish a degree of trust, untrust, mistrust and distrust in answers if the answers are provided without any kind of justification • Knowledge Provenance (KP) is a description of both the origins of knowledge and the reasoning process to produce an answer • Users may need KP to establish a degree of trust in the answer • Which sources were used? • Who are the authors of each sources? • Which engines (i.e., agents) were used? • What are the assumptions of each engine? Are the engines’ rules sound? • KP itself may not be enough for trusting the answer • I may know nothing about one or more of the sources in the KP • I may have no information about the reliability of one or more of then engines in the KP

  3. Trusting Answers from the Web • The overall process of establishing a degree of trust in answers from web applications is particularly complex since applications may rely on: • Hybrid and distributed processing, e.g., web services, the Grid • Large number of heterogeneous, distributed information sources, e.g., the Web • information sources with more variation in their reliability, e.g., information extraction • Sophisticated information integration methods, e.g., SIMS, TSIMMIS • The definition of trust is a significant part of the process • The task of keeping, encoding, sharing and gathering KP for answers is another part of the process • The use of KP to derive trust values for answers is yet another part of the process

  4. The Inference Web • The Inference Web is an infrastructure supporting explanations for answers from the web • The Proof Markup Language (PML) is used to encode answer justification, i.e., information manipulation traces, proofs • IWBase is used to annotate PML documents with proof-related data, i.e., trust values for sources and engines • User U1 asks question Q • {A1,A2,…,An} is an answer set for Q PML Documents IWBase S1 A1 IE1 Q(U1) S2 A2 ... ... S3 An IE2

  5. Inference Web and KP Inference Web supports KP for answers derived by multiple methods • Information extraction –IBM (UIMA), Stanford (TAP) • Information integration –USC ISI (Prometheus/Mediator); Rutgers University (Prolog/Datalog) • Task processing –SRI International (SPARK) • Theorem proving • First-Order Theorem Provers –SRI International (SNARK); Stanford (JTP); University of Texas, Austin (KM) • SATisfiability Solvers –University of Trento (J-SAT) • Expert Systems –University of Fortaleza (JEOPS) • Service composition – Stanford, University of Toronto, UCSF (SDS) • Semantic matching –University of Trento (S-Match) • Debugging ontologies – University of Maryland, College Park (SWOOP/Pellet) • Problem solving –University of Fortaleza (ExpertCop)

  6. IW TrustNet t6-7 t7-S1 u7 u6 t7-IE1 t6-3 t4-S4 t3-4 u4 u3 S4 t5-6 t4-S3 t1-3 t1-5 t1-IE2 u1 u5 IW Trust Framework The Inference Web Trust (IWTrust) • IWTrust extends the Inference Web to support trust computation • IW TrustNet is a social network of recommenders • A component computing trust values for answers • Trust values are used to rank answers and answer justifications • User U1 trusts U3 to a degree t1-3 PML Documents IWBase S1 (A1, t11, t12,...) IE1 Q(U1) S2 (A2, t21, t22,...) ... ... S3 (An, tn1, tn2,...) IE2

  7. http://www.w3.org/2004/Talks/0412-RDF-functions/slide4-0.htmlhttp://www.w3.org/2004/Talks/0412-RDF-functions/slide4-0.html Conclusions • IWTrust provides infrastructure for building a trust graph from users asking questions to answers • Knowledge provenance is a key element of the trust graph and a requirement for trusting answers in general • Inference Web is a Semantic Web solution for knowledge provenance iw.stanford.edu • IWTrust intends to be a solution for the Semantic Web trust layer • Inference Web is a solution for the Semantic Web proof layer

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