Abstract
Scientific/Academic events promote the meeting of researchers for the dissemination of their work to a scientific community. These events are dynamic, where several sessions can happen simultaneously and participants may have difficulty choosing which sessions to attend. Recommender Systems can support participants in this choice by offering recommendations based on information from sessions, participants’ profile and social relationships. This paper presents a Social Recommendation Model of Technical Sessions for Scientific Events. The model was partially implemented and was applied on the IHC 2017 and IHC 2018 events, considering co-authoring relationships. The application of the model was evaluated via a questionnaire and triangulated through captured usage data, where users provided their perceptions about the utility of coauthoring network to recommend sessions. Results suggest the model is promising and capable of supporting the implementation of relevant social recommendation mechanisms.
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Acknowledgment
We thank the financial support of FAPESC, public call public FAPESC/CNPQ No. 06/2016 support the infrastructure of CTI for young researchers, project T.O. No: 2017TR1755 - Intelligent Educational Environments with Integration of Learning Analytics and Gamification Techniques. The present work was carried out with the support of the Coordination of Improvement of Higher Education Personnel - Brazil (CAPES) - Financing Code 001.
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Appendix - Recommendation Evaluation Questionnaire
Appendix - Recommendation Evaluation Questionnaire
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Tramontin, A., Pereira, R., Gasparini, I. (2020). What to See in a Scientific Event? A Social Recommendation Model of Technical Sessions. In: Santos, R., Maciel, C., Viterbo, J. (eds) Software Ecosystems, Sustainability and Human Values in the Social Web. WAIHCWS WAIHCWS 2017 2018. Communications in Computer and Information Science, vol 1081. Springer, Cham. https://doi.org/10.1007/978-3-030-46130-0_6
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DOI: https://doi.org/10.1007/978-3-030-46130-0_6
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