Identifying recommendation opportunities for computer-supported collaborative environments

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URI: https://hdl.handle.net/11556/3287
ISSN: 0266-4720
DOI: 10.1111/exsy.12159
Publication date
2016-10-01
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Abstract
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.
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Publisher Copyright: © 2016 Wiley Publishing Ltd
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asynchronous interaction , collaborative systems , computer-supported collaborative work , data mining , Control and Systems Engineering , Theoretical Computer Science , Computational Theory and Mathematics , Artificial Intelligence
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journal article
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Lobo , J L , Santos , O C , Boticario , J G & Del Ser , J 2016 , ' Identifying recommendation opportunities for computer-supported collaborative environments ' , Expert Systems , vol. 33 , no. 5 , pp. 463-479 . https://doi.org/10.1111/exsy.12159