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Identifying recommendation opportunities for computer‐supported collaborative environments
Author(s) -
Lobo Jesus L.,
Santos Olga C.,
Boticario Jesus G.,
Del Ser Javier
Publication year - 2016
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12159
Subject(s) - computer science , generality , transferability , collaborative filtering , focus (optics) , collaborative learning , recommender system , human–computer interaction , data science , knowledge management , world wide web , psychology , machine learning , physics , logit , optics , psychotherapist
Collaborative indicators derived from participants' interactions can be used to support and improve their collaborative behaviour. In this research, we focus on automatically identifying recommendation opportunities in the Collaborative Logical Framework from participants' interactions. Different information sources have been considered: (a) statistical collaborative indicators; (b) social interactions; (c) opinions received by the participants via ratings; and (d) users' affective state and personality. The recommendations have been elicited considering the generality and transferability of the participants' interactions provided by the Collaborative Logical Framework. As a result, three scenarios have been identified that lead us to propose meaningful grouping suggestions and recommendations, which ultimately aimed to ground an informed personalized support to the participants in intensive collaborative frameworks.