Research output per year
Research output per year
Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review
This paper presents the motivation, concepts, ideas and research questions underlying a PhD research project in the domain of recommender systems, and more specifically on multi-criteria recommendation. While we build on the existing work in this direction, we aim at introducing recommendation frameworks that do not only optimize for different criteria simultaneously, but also exploit their interrelations. For this aim, we will address three multi-criteria recommendation challenges, namely multi-modal user and item modeling, package recommendation, and user-centric recommendation. For realizing these frameworks, and in particular, for learning interactions and interrelations in the criteria space, we will rely on the state-of-the-art deep learning systems, and in particular the Generative Adversarial Networks (GANs). In addition, a novel evaluation strategy for multi-criteria recommendation targeting the maximization of the user's satisfaction will also be devised.
Original language | English |
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Title of host publication | RecSys '18 |
Subtitle of host publication | Proceedings of the 12th ACM Conference on Recommender Systems |
Place of Publication | New York, NY |
Publisher | Association for Computer Machinery |
Pages | 553-557 |
Number of pages | 5 |
ISBN (Print) | 978-1-4503-5901-6 |
DOIs | |
Publication status | Published - 2018 |
Event | 12th ACM Conference on Recommender Systems, RecSys 2018 - Vancouver, Canada Duration: 2 Oct 2018 → 7 Oct 2018 |
Conference | 12th ACM Conference on Recommender Systems, RecSys 2018 |
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Country/Territory | Canada |
City | Vancouver |
Period | 2/10/18 → 7/10/18 |
Research output: Thesis › Dissertation (TU Delft)