![]() Yilma, Bereket Abera ![]() ![]() in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23) (2023, April) Artwork recommendation is challenging because it requires understanding how users interact with highly subjective content, the complexity of the concepts embedded within the artwork, and the emotional and ... [more ▼] Artwork recommendation is challenging because it requires understanding how users interact with highly subjective content, the complexity of the concepts embedded within the artwork, and the emotional and cognitive reflections they may trigger in users. In this paper, we focus on efficiently capturing the elements (i.e., latent semantic relationships) of visual art for personalized recommendation. We propose and study recommender systems based on textual and visual feature learning techniques, as well as their combinations. We then perform a small-scale and a large-scale user-centric evaluation of the quality of the recommendations. Our results indicate that textual features compare favourably with visual ones, whereas a fusion of both captures the most suitable hidden semantic relationships for artwork recommendation. Ultimately, this paper contributes to our understanding of how to deliver content that suitably matches the user's interests and how they are perceived. [less ▲] Detailed reference viewed: 185 (41 UL)![]() Leiva, Luis A. ![]() ![]() ![]() Book published by Springer (2022) Detailed reference viewed: 60 (1 UL)![]() Leiva, Luis A. ![]() in ACM Transactions on Intelligent Systems and Technology (2022) Detailed reference viewed: 37 (1 UL)![]() Leiva, Luis A. ![]() in Universal Access in the Information Society (2022) Detailed reference viewed: 40 (2 UL)![]() Latifzadeh, Kayhan ![]() ![]() in Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (2022) Detailed reference viewed: 45 (16 UL)![]() Dubiel, Mateusz ![]() ![]() in Conversational Agents Trust Calibration: A User-Centred Perspective to Design (2022) Previous work identified trust as one of the key requirements for adoption and continued use of conversational agents (CAs). Given recent advances in natural language processing and deep learning, it is ... [more ▼] Previous work identified trust as one of the key requirements for adoption and continued use of conversational agents (CAs). Given recent advances in natural language processing and deep learning, it is currently possible to execute simple goal-oriented tasks by using voice. As CAs start to provide a gateway for purchasing products and booking services online, the question of trust and its impact on users’ reliance and agency becomes ever-more pertinent. This paper collates trust-related literature and proposes four design suggestions that are illustrated through example conversations. Our goal is to encourage discussion on ethical design practices to develop CAs that are capable of employing trust-calibration techniques that should, when relevant, reduce the user’s trust in the agent. We hope that our reflections, based on the synthesis of insights from the fields of human-agent interaction, explainable ai, and information retrieval, can serve as a reminder of the dangers of excessive trust in automation and contribute to more user-centred CA design. [less ▲] Detailed reference viewed: 94 (16 UL)![]() Dubiel, Mateusz ![]() ![]() ![]() Scientific Conference (2022) Detailed reference viewed: 92 (20 UL)![]() ; Leiva, Luis A. ![]() in ACM Transactions on Interactive Intelligent Systems (2022), 12(1), Detailed reference viewed: 85 (13 UL)![]() ; ; et al in Extended Abstracts of the SIGCHI Conference on Human Factors in Computing Systems (CHI EA) (2022) Detailed reference viewed: 43 (2 UL)![]() ; ; et al in Proceedings of the ACM on Human-Computer Interaction (2022) Detailed reference viewed: 87 (8 UL)![]() ; ; et al in Proceedings of the ACM Conference on Intelligent User Interfaces (IUI) (2022) Detailed reference viewed: 37 (2 UL)![]() Leiva, Luis A. ![]() in Interacting with Computers (2021) Detailed reference viewed: 77 (8 UL)![]() Leiva, Luis A. ![]() in Proceedings of the ACM International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) (2021) Detailed reference viewed: 192 (2 UL)![]() ; Leiva, Luis A. ![]() in Journal of Chemical Education (2021) Detailed reference viewed: 72 (1 UL)![]() Leiva, Luis A. ![]() ![]() ![]() Book published by BnL (2021) Detailed reference viewed: 219 (31 UL)![]() ; Leiva, Luis A. ![]() in IEEE Transactions on Human-Machine Systems (2021), 51(6), Detailed reference viewed: 63 (2 UL)![]() ; Leiva, Luis A. ![]() in Sensors (2021), 21(17), Detailed reference viewed: 67 (3 UL)![]() ; Leiva, Luis A. ![]() in Proceedings of the ACM Conference on Designing Interactive Systems (DIS) (2021) Detailed reference viewed: 53 (7 UL)![]() ; ; Leiva, Luis A. ![]() in Sensors (2021), 21(9), Detailed reference viewed: 90 (9 UL)![]() ; ; Leiva, Luis A. ![]() in Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (2021) Detailed reference viewed: 210 (16 UL) |
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