Use of Social Elements for the Recommendation of Sessions in Academic Events

  • Aline de P. A. Tramontin UDESC
  • Isabela Gasparini UDESC
  • Roberto Pereira UFPR

Abstract


Scientific events bring together a large number of researchers and are composed of different types of sessions, which can cause an overload of attention and difficulty in deciding which sessions to participate. To lessen such problems, Recommender Systems can assist the user by offering options that are appropriate for each attendee. This paper presents a proposal for recommending sessions of academic/scientific events based on social elements. The recommendations are supported by the academic events' co-authoring network to improve the quality of session recommendation based on the users' previous publications. For authors/participants who do not have publications in previous editions of the corresponding event, the recommendations will be generated through the Collaborative Filtering approach.
Keywords: Recommender Systems, Social Context, Social Recommender Systems, Co-authorship Network, Scientific Event
Published
2017-12-26
How to Cite

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TRAMONTIN, Aline de P. A.; GASPARINI, Isabela; PEREIRA, Roberto. Use of Social Elements for the Recommendation of Sessions in Academic Events. In: WORKSHOP ON ASPECTS OF HUMAN-COMPUTER INTERACTION FOR THE SOCIAL WEB (WAIHCWS), 8. , 2017, Joinville. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2017 . p. 48-57. ISSN 2596-0296.