Trust Calculation

Semantic Agreement for Ontology Integration
  • Dennis Hooijmaijers
  • Markus Stumptner
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 228)


The Semantic Web is generally envisioned as a vast collection of document embedded knowledge that makes it highly improbable for agents traversing this space to know directly what entity, person, or organisation they are dealing with. In such an environment, the explicit representation of trust becomes an intrinsic part of calculating whether an agent can believe and use (or reuse) foreign sources. A key activity in this process is the step of integrating an agent’s ontology with that of another document found on the Web. To assist in calculating trust values for this purpose, Riposte provides a set of trust models and trust manipulation algorithms to create a dynamic model of author trust based on work that is being provided to an agent. Riposte is an ontology integration tool that uses suggestions and bases trust on whether an object in the provided ontology confirms or refutes current beliefs. The author can be assigned an initial trust value and this value is recalculated after the integration process.


Ontology Bayesian Network Trust 


  1. Bertino, E., Ferrari, E., and Squicciarini, A, (2004). Trust negotiations: concepts, systems, and languages. Computing in Science and Engineering, 06(4):27–34.CrossRefGoogle Scholar
  2. Ding, L., Zhou, L., and Finin, T. (2003). Trust based knowledge outsourcing for Semantic Web agents. In Proc. IEEE/WIC, pages 379–387.Google Scholar
  3. Ding, Zhongli and Peng, Yun (2004). A probabilistic extension to ontology language OWL. In Proc. of the Hawaii International Conference on System Sciences., pages 1775–1784.Google Scholar
  4. Dou, Dejing, McDermott, Drew, and Qi, Peishen. (2003). Ontology translation on the Semantic Web. In Proc. ODBASE’03, pages 952–969.Google Scholar
  5. Dumbill, Ed (2002). XML watch: Finding friends with XML and RDF. IBM’s XML Watch.Google Scholar
  6. Golbeck, Jennifer, Parsia, Bijan, and Hendler, James (2003). Trust networks on the Semantic Web. In 7th International Workshop, CIA 2003, LNAI 2782, pages 238–249.Google Scholar
  7. Gonzalez, Avelino J. and Dankel, Douglas D. (1993). The engineering of knowledge-based systems; theory and practice. Prentice Hall.Google Scholar
  8. Guha, R. V. (2003). Open rating systems. Technical report, Stanford Knowledge System Laboratory.Google Scholar
  9. Guha, R. V., Kumar, R., Raghavan, P., and Tomkins, A. (2004). Propagation of trust and distrust. In Proc. WWW. Google Scholar
  10. Hooijmaijers, Dennis and Bright, Damien (2005). Uncertain knowledge gathering: an evolutionary approach. In Proc. ISMIS 05, Saratoga Springs NY. Springer-Verlag.Google Scholar
  11. Huang, Jingwei and Fox, M.S. (2005). Trust judgment in knowledge provenance. In Proc. DEXA, 2005, pages 524–528.Google Scholar
  12. Jaeger, Manfred (1994). Probabilistic reasoning in Terminological Logics. In Proc. KR Conf..Google Scholar
  13. Luger, G. F. (2002). Artificial Intelligence Structures and Strategies for Complex Problem Solving. Addison Wesley, 4th edition.Google Scholar
  14. McGuinness, D.L., Fikes, R., Rice, J., and Wilder, S. (2000). The Chimaera ontology environment. In Proc. AAAI. Google Scholar
  15. Noy, N. F., Guha, R. V., and Musen, M. A. (2005). User ratings of ontologies: Who will rate the raters? In Proc. AAAI. Google Scholar
  16. Noy, N. F., Mitra, P., and Jaiswal, A. R. (2004). OMEN: A probabilistic ontology mapping tool. In Proc. ISWC’ 04. Google Scholar
  17. Noy, N. F. and Musen, M. A. (1999). An algorithm for merging and aligning ontologies: Automation and tool support. In Proc. AAAI. Google Scholar
  18. Pearl, Judea (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann.Google Scholar
  19. Staab, S., Domingos, P., Mike, P., Golbeck, J., Ding, Li, Finin, T., Joshi, A., Nowak, A, and Vallacher, R.R. (2005). Social networks applied. IEEE Intelligent Systems, 20(1):80–93..CrossRefGoogle Scholar
  20. Ziegier, Cai-Nicolas and Lausen, Georg (2004). Spreading activation models for trust propagation. In Proc. EEE 2004.Google Scholar

Copyright information

© International Federation for Information Processing 2006

Authors and Affiliations

  • Dennis Hooijmaijers
    • 1
  • Markus Stumptner
    • 1
  1. 1.ACRCUniversity of SAAustralia

Personalised recommendations