Open this publication in new window or tab >>2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]
Recommender systems are algorithmic tools that assist users in discovering relevant items from a wide range of available options. Along with the apparent user value in mitigating the choice overload, they have an important business value in boosting sales and customer retention. Last, but not least, they have brought a substantial research value to the algorithm developments of the past two decades, mainly in the academic community. This thesis aims to address some of the aspects that are important to consider when recommender systems pave their way towards real-life applications.
Place, publisher, year, edition, pages
Malmö: Malmö universitet, 2020. p. 238
Series
Studies in Computer Science ; 9
Keywords
recommender systems, recommendations, matchmaking, recommendation ethics
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-13750 (URN)10.24834/isbn.9789178770755 (DOI)978-91-7877-074-8 (ISBN)978-91-7877-075-5 (ISBN)
Public defence
2020-05-08, Auditorium C, C0E11, Niagara buildning, Nordenskiöldsgatan 1, Malmö, 13:00 (English)
Opponent
Supervisors
2020-03-112020-03-082024-02-27Bibliographically approved