Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems – An Approach

Markus Jäger, Trong Nhan Phan, Christian Huber, Josef Küng

Research output: Conference proceeding/Chapter in Book/Report/Chapterpeer-review

Abstract

The origin of data (data provenance), should always be measured or categorized within the context of trusting the source of data. Can we be sure that the information we receive is trustworthy and reliable? Is the source trustable? Is the data certain? And how important is the received data the our current and next step of processing? We face these questions in the context of knowledge processing systems by developing a convenient approach to bring all these questions and values – trustability, certainty, importance – into a computable, measurable, and comparable way of expression. Not yet facing the question “How to compute trust or certainty?”, but how to incorporate and process their measured values in knowledge processing systems to receive a representative view on the whole environment and its output.
Original languageEnglish
Title of host publicationFuture Data and Security Engineering
DOIs
Publication statusPublished - 2016

Keywords

  • Trust
  • Certainty
  • Knowledge processing systems
  • security
  • Risk
  • Provenance
  • Reliability

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