TL;DR
This paper explores how to determine the reliability of information sources based on previous data merging outcomes, enabling improved future data integration from multiple sensors or sources.
Contribution
It introduces a method for inferring source reliability from prior belief merging results, rather than assuming known or static reliability measures.
Findings
Reliability of sources can be inferred from previous merging outcomes.
The approach allows dynamic adjustment of source trustworthiness.
Enhances data integration accuracy in sensor networks.
Abstract
A common assumption in belief revision is that the reliability of the information sources is either given, derived from temporal information, or the same for all. This article does not describe a new semantics for integration but the problem of obtaining the reliability of the sources given the result of a previous merging. As an example, the relative reliability of two sensors can be assessed given some certain observation, and allows for subsequent mergings of data coming from them.
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