Combining User Reputation and Provenance Analysis for Trust Assessment

Davide Ceolin, Paul Groth, Valentina Maccatrozzo, Wan Fokkink, Willem Robert Van Hage, Archana Nottamkandath
2016 Journal of Data and Information Quality  
Trust is a broad concept which, in many systems, is often reduced to user reputation alone. However, user reputation is just one way to determine trust. The estimation of trust can be tackled from other perspectives as well, including by looking at provenance. Here, we present a complete pipeline for estimating the trustworthiness of artifacts given their provenance and a set of sample evaluations. The pipeline is composed of a series of algorithms for: (1) extracting relevant provenance
more » ... s, (2) generating stereotypes of user behavior from provenance features, (3) estimating the reputation of both stereotypes and users, (4) using a combination of user and stereotype reputations to estimate the trustworthiness of artifacts and, (5) selecting sets of artifacts to trust. These algorithms rely on the W3C PROV recommendations for provenance and on evidential reasoning by means of subjective logic. We evaluate the pipeline over two tagging datasets: tags and evaluations from the Netherlands Institute for Sound and Vision's Waisda? video tagging platform; and crowdsourced annotations from the Steve.Museum project. The approach achieves up to 85% precision when predicting tag trustworthiness. Perhaps more importantly, the pipeline provides satisfactory results using relatively little evidence through the use of provenance. ACM Reference Format:
doi:10.1145/2818382 dblp:journals/jdiq/CeolinGMFHN16 fatcat:p7356gjszbgv7c6tvbyryay7ty