Recommender Systems as the Lens of Life - CyCAT Webinar

Ημερομηνία :
Έναρξη 24/05/2019
Λήξη 24/05/2019
Ώρα 15:00
Τόπος διεξαγωγής :
 
Είδος εκδήλωσης :
 Ομιλία
Ηλεκτρονική σελίδα εκδήλωσης :
 
  _self

Το Ερευνητικό Κέντρο Αλγοριθμικής Διαφάνειας CyCAT με έδρα το Ανοικτό Πανεπιστήμιο Κύπρου οργανώνει διαδικτυακό σεμινάριο με θέμα "How Personalized, Adaptive and Dangerous is Persuasive Technology?" και ομιλητή τον  Dr Frank Hopfgartner,  Senior Lecturer in Data Science, Information School, University of Sheffield.

📅  Παρασκευή, 24 Mαΐου 2019, ώρα έναρξης: 15:00 (GMT +2 / Cyprus)

Η διάλεξη θα μεταδίδεται μέσω της διαδικτυακής πλατφόρμας του ΑΠΚΥ https://video.ouc.ac.cy/Panopto/Pages/Home.aspx κατόπιν εγγραφής στο: https://forms.gle/ZAcPonZwMZvvuSgA8.

Θα δοθούν βεβαιώσεις παρακολούθησης. 
 
 Frank Hopfgartner

Dr Frank Hopfgartner is a Senior Lecturer in Data Science at the Information School of University of Sheffield. His research to date can be placed in the intersection of information systems (e.g., information retrieval and recommender systems), content analysis and data science. He has (co-) authored over 150 publications in above mentioned research fields, including a book on smart information systems, various book chapters and papers in peer-reviewed journals, conferences and workshops. To date, he has successfully acquired over £1 Million in research funding from national and international sources to support his research.
 
He gained manifold work experience at research-led science & engineering centers in the US, Ireland, and Germany, as well as at leading universities in Germany, China, and the UK. Building on this experience, a further theme of his work is to bridge the gap between academia and industry, e.g., by collaborating closely with industry to incorporate real-world challenges in his teaching, or by creating opportunities for academics to benefit from companies’ resources or expertise.

Presentation Abstract: 

Increasingly, algorithms have a strong impact on how we experience the world around us. For example, recommendation algorithms are used to point us to products we might want to buy online, restaurants we should try, or even news articles we might be interested in. As convenient as such recommendations can be, the required automated filtering of content comes with consequences. In this talk, Dr. Hopfgartner will first briefly introduce the most common algorithms used by modern recommender systems. Moreover, he will discuss current limitations and pitfalls of recommender systems. Finally, he will outline a vision on recommendations as the Lens of Life.