A Social Recommendation Template for Presentations Sessions for Scientific Events

Abstract

Scientific/Academic events promote the meeting of researchers for the dissemination of their work to the scientific community. These events are dynamic, sessions can happen simultaneously, and in this case participants may have difficulty choosing which sessions attend. Recommender Systems can aid the participant in this choice, as they use information from the sessions, participants and information about the participants' social relationships. The goal of this work is to present the proposal of a Model of Social Recommendation for Scientific Events, which can be applicable to any type of scientific event. The model was partially implemented and was applied for the IHC 2017 event, for this, co-authoring relationships were considered. The instantiated model was evaluated through a questionnaire, where we evaluated users' perceptions about the utility of coauthoring indication to recommend sessions.