{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:ece_etds-1230"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:ece_etds-1230","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"Automating the moderation process in GEO using trust metrics","abstract":"Distributed knowledge bases offer novel and fascinating ways to build, integrate and process knowledge. In these distributed knowledge bases, many users collaborate and contribute content. Verification and validation of the user's contributions become imperative for the success of these knowledge bases, especially if it is a scientific knowledge base. However, manually verifying and moderating the contributions become a bottleneck for an up-to-date system. In this thesis, we propose an algorithm to automate the moderation process and we implement the algorithm in an open scientific knowledge base application called Global Energy Observatory (GEO). Using Trust Metrics, user's contributions can be automatically accepted without waiting for the moderators to verify and validate them. This provides users with a smooth, hassle free experience when they contribute data. We also provide empirical analysis to substantiate our algorithm. An open information exchange architecture, that makes use of Semantic Web formats is also presented.","abstract_html":"Distributed knowledge bases offer novel and fascinating ways to build, integrate and process knowledge. In these distributed knowledge bases, many users collaborate and contribute content. Verification and validation of the user&#x27;s contributions become imperative for the success of these knowledge bases, especially if it is a scientific knowledge base. However, manually verifying and moderating the contributions become a bottleneck for an up-to-date system. In this thesis, we propose an algorithm to automate the moderation process and we implement the algorithm in an open scientific knowledge base application called Global Energy Observatory (GEO). Using Trust Metrics, user&#x27;s contributions can be automatically accepted without waiting for the moderators to verify and validate them. This provides users with a smooth, hassle free experience when they contribute data. We also provide empirical analysis to substantiate our algorithm. 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