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Evidential uncertainties on rich labels for active learning
Recent research in active learning, and more precisely in uncertainty sampling, has focused on the decomposition of model uncertainty into reducible and irreducible uncertainties.
Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing context
To overcome this problem, we propose a method, MONITOR, which estimates the contributor's profile and aggregates the collected data by taking into account their possible imperfections thanks to the theory of belief functions.
Modelisation de l'incertitude et de l'imprecision de donnees de crowdsourcing : MONITOR
Crowdsourcing is defined as the outsourcing of tasks to a crowd of contributors.
Contributors profile modelization in crowdsourcing platforms
The crowdsourcing consists in the externalisation of tasks to a crowd of people remunerated to execute this ones.
Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People
The purpose of this study is to provide an accessibility measure of web-pages, in order to draw disabled users to the pages that have been designed to be ac-cessible to them.
