Personalised automated assessments

Consider a person who needs to assess a large amount of information. For instance, think of a teacher of a massive open online course with thousands of enrolled students, or a senior program committee member in a large conference who needs to decide what are the final marks of reviewed papers, or a buyer in an e-commerce scenario who needs to build up her opinion about products. When assessing a large number of objects, sometimes it is simply unfeasible to evaluate them all and very often one needs to rely on the opinions of others. In this paper, we provide a model that uses peer assessments (assessments made by others) in an online community to approximate the assessments that a particular member of the community would generate given the occasion to do so (e.g. the tutor, the SPC member or the buyer—we refer to this person as the leader). Furthermore, we provide a measure of the uncertainty of the computed assessments and a ranking of the objects that should be assessed next. The model, although inspired by human societies is thought to be used in the organisation of agent communities.