Strategies for truth discovery under resource constraints

Abstract

We present a decision-theoretic approach for sampling information sources in resource-constrained environments, where there is uncertainty regarding source trustworthiness. We exploit diversity among sources to stratify the population into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of source collusion. We show through empirical evaluation that our model is as effective as existing truth discovery approaches with respect to accuracy, while significantly reducing sampling cost.