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Incomplete knowledge   Center for Computational Intelligence, Learning, and Discovery Artificial Intelligence Research Laboratory Department of Computer Science Acknowledgements :  This work is supported in part by grants from the National Science Foundation  (IIS-0639230). Privacy-Preserving Reasoning on the Semantic Web Jie Bao, Giora Slutzki, and Vasant Honavar 3- Concrete Strategies 2 – General Strategy Highlights :  ,[object Object],[object Object],1 – Problem Description ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Locally visible : Has date Query:  Has date? Answer :  Unknown Query:  Has travel? Answer: Unknown Query:  Busy (has activity)? Answer : Yes Hidden knowledge   ,[object Object],[object Object],[object Object],[object Object],[object Object],EXAMPLE :  a calendar ontology FOR HIERARCHIES :  FOR DESCRIPTION LOGICS (AND OWL) :  Reasoning Strategy : Safety Scope : “ safe” graph “ unsafe” graph Basic idea : Problem reduces to graph reachability analysis Basic idea : Ensure that answers to queries will NOT give knowledge beyond Critical visible knowledge (i.e.,  K v  about the signature of  K h .) K h K v Critical visible knowledge  K vc C   ⊑  D C   ⊑   R. D G  ⊑ H ,[object Object],Reference: Bao, J., Slutzki, G., and Honavar, V. (2007).  Privacy-Preserving Reasoning on the Semantic Web  . In Web Intelligence 2007. a b c d e a b c d e

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Privacy-Preserving Reasoning on the Semantic Web (Poster)

  • 1.