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|Title: ||Knowledge Provenance: An Approach to Modeling and Maintaining The Evolution and Validity of Knowledge|
|Authors: ||Huang, Jingwei|
|Advisor: ||Fox, Mark|
|Department: ||Mechanical and Industrial Engineering|
|Keywords: ||Knowledge Provenance|
|Issue Date: ||28-Jul-2008|
|Abstract: ||The Web has become an open decentralized global information / knowledge repository, a platform for distributed computing and global electronic markets, where people are confronted with information of unknown sources, and need to interact with “strangers”. This makes trust and the validity of information in cyberspace arise as crucial issues.
This thesis proposes knowledge provenance (KP) as a formal approach to determining the origin and validity of information / knowledge on the Web, by means of modeling and maintaining the information sources, information dependencies, and trust structures. We conceptualize and axiomatize KP ontology including static KP and dynamic KP. The proposed KP ontology, provides a formal representation of linking trust in information creators and belief in the information created; lays a foundation for further study of knowledge provenance; provides logical systems for provenance reasoning by machines. The web ontology of KP can be used to annotate web information; and KP reasoner can be used as a tool to trace the origin and to determine the validity of Web information.
Since knowledge provenance is based on trust in information sources, this thesis also proposes a logical theory of trust in epistemic logic and situation calculus. In particular, we formally define the semantics of trust; from it, we identify two types of trust: trust in belief and trust in performance; reveal and prove that trust in belief is transitive; trust in performance is not, but by trust in belief, trust in performance can propagate in social networks; by using situation calculus in trust formalization, the context of trust is formally represented by reified fluents; we also propose a distributed logical model for trust reasoning using social networks, by which each agent’s private data about trust relationships can be protected. This study provides a formal theoretical analysis on the transitivity of trust, which supports trust propagation in social networks. This study of trust supports not only knowledge provenance but also the general trust modeling in cyberspace.|
|Appears in Collections:||Doctoral|
Department of Mechanical & Industrial Engineering - Doctoral theses
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