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 , where the users are authors from research papers, the items are scientific items, such as chemical compounds, genes, or phenotypes, and the ratings are the number of papers an author wrote about an item. We have now as case studies a dataset in the field of Astronomy, and a dataset in the field of Chemistry. With these dataset available, it is now possible to start testing and developing new recommender algorithms. Thus, this seminar will present a Hybrid recommender model for recommending Chemical Compounds. The Hybrid model integrates state-of-the-art collaborative-filtering algorithms for implicit feedback and a new content-based algorithm, based on the semantic similarity between the Chemical Compounds in the ChEBI ontology. This model was evaluated using the dataset of implicit feedback of Chemical Compounds, CheRM, created through LIBRETTI.

More information: https://moodle.ciencias.ulisboa.pt/course/view.php?id=2228#section-2.

z(r)oom: https://videoconf-colibri.zoom.us/j/98030464254.

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.