Uso de Elementos Sociais para a Recomendação de Sessões em Eventos Acadêmicos

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

Resumo

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.

Palavras-chave: Recommender Systems, Social Context, Social Recommender Systems, Co-authorship Network, Scientific Event