|Roberto Centeno: "From blurry numbers to clear preferences: A mechanism to extract reputation in social networks"|
Fecha: martes 16 de julio de 2013
Lugar de celebración: Sala 1.03, ETSI Informática, UNED
Complex social networks are typically used in order to represent and structure social relationships that do not follow a predictable pattern of behaviour. Due to its openness and dynamics, those networks make participants continuously deal with uncertainty before any type of interaction. Reputation appears as a key concept helping users to mitigate such uncertainty. However, most of the reputation mechanisms proposed in the literature suffer from problems such as the subjectivity in the opinions and their consequent inaccurate aggregation. With these problems in mind, we present a reputation mechanism based on the concepts of pairwise elicitation processes and knock-out tournaments. The main objective of this mechanism is to build reputation rankings from qualitative opinions, so getting rid of the subjectivity problems associated with the aggregation of quantitative opinions.
Roberto Centeno is Teaching Assitant and researcher at UNED's LTCS Group. His research background is on distributed artificial intelligence. In particular his main interests are focused on the regulation of Open MultiAgent Systems and the study of social aspects such as trust and reputation and its application on both social networks and eLearning theories. Currently he's working on topics such as Open Multi-Agent Systems, Organisational models, Normative systems, Regulation through incentives, Trust and reputation mechanisms, Social networks and eLearning.
Lugar de celebraciónSala 1.03ETSI Informática, UNEDc/ Juan del Rosal, 16Ciudad Universitaria28040 Madrid