Speaker: Márcia Barros.
Abstract: Recommender systems have been widely used in fields such as movies, music and online stores, however, they are poorly applied to scientific fields. We identified as one of the main challenges for using recommender systems in scientific fields, the lack of datasets suitable for evaluating recommender algorithms. In previous work, we overcame this challenge by developing a new methodology called LIBRETTI (LIterature Based RecommEndaTion of scienTific Items). LIBRETTI allows the creation of standard datasets of implicit feedback with the format of
Seminars of the PhD in Informatics 2019/2020
PhD students, faculty, MSc and BSc students, are all invited to attend. This is an excellent opportunity for cross-disciplinary development through presentation and discussion of edge research going on in our department.
Please make space in your agenda an save the date, even if the subject is apparently not directly related to your research. You may be surprised with the bridging opportunities that pop up, and the PhD student will benefit from comments that we all can make.
Moreover, we all should adopt the scientific culture of attending our most advanced regular seminars and of providing our feedback to the speakers.