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Barile, Francesco (author), Draws, T.A. (author), Inel, Oana (author), Rieger, A. (author), Najafian, S. (author), Ebrahimi Fard, Amir (author), Hada, Rishav (author), Tintarev, N. (author)Social choice aggregation strategies have been proposed as an explainable way to generate recommendations to groups of users. However, it is not trivial to determine the best strategy to apply for a specific group. Previous work highlighted that the performance of a group recommender system is affected by the internal diversity of the group...journal article 2023
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Vrijenhoek, Sanne (author), Michiels, Lien (author), Kruse, Johannes (author), Starke, Alain (author), Viader Guerrero, J. (author), Tintarev, Nava (author)Recommender systems are among the most widely used applications of artificial intelligence. Since they are so widely used, it is important that we, as practitioners and researchers, think about the impact these systems may have on users, society, and other stakeholders. To that effect, the NORMalize workshop seeks to introduce normative thinking...conference paper 2023
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Musto, Cataldo (author), Tintarev, N. (author), Inel, O. (author), Polignano, Marco (author), Semeraro, Giovanni (author), Ziegler, Jürgen (author)Adaptive and personalized systems have become pervasive technologies that are gradually playing an increasingly important role in our daily lives. Indeed, we are now used to interact every day with algorithms that help us in several scenarios, ranging from services that suggest us music to be listened to or movies to be watched, to personal...conference paper 2021
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Mulder, M. (author), Inel, O. (author), Oosterman, J.E.G. (author), Tintarev, N. (author)Diversity in personalized news recommender systems is often defined as dissimilarity, and operationalized based on topic diversity (e.g., corona versus farmers strike). Diversity in news media, however, is understood as multiperspectivity (e.g., different opinions on corona measures), and arguably a key responsibility of the press in a...conference paper 2021
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Jin, Yucheng (author), Tintarev, N. (author), Htun, Nyi Nyi (author), Verbert, Katrien (author)Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of...journal article 2019
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Sullivan, Emily (author), Bountouridis, D. (author), Harambam, Jaron J. (author), Najafian, S. (author), Loecherbach, Felicia (author), Makhortykh, Mykola (author), Kelen, Domokos (author), Wilkinson, Daricia (author), Graus, David (author), Tintarev, N. (author)Personalized content provided by recommender systems is an integral part of the current online news reading experience. However, news recommender systems are criticized for their'black-box' approach to data collection and processing, and for their lack of explainability and transparency. This paper focuses on explaining user profiles...conference paper 2019
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Ghanmode, Ishan (author), Tintarev, N. (author)This paper introduces and evaluates a novel interface, MovieTweeters. It is a movie recommendation system which incorporates social information with a traditional recommendation algorithm to generate recommendations for users. Few previous studies have investigated the influence of using social information in interactive<br/>interfaces to...conference paper 2018
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Tintarev, N. (author), Rostami, Shahin (author), Smyth, Barry (author)In this paper we consider how to help users to better understand their consumption profiles by examining two approaches to visualising user profiles - chord diagrams, and bar charts - aimed at revealing to users those regions of the recommendation space that are unknown to them, i.e. blind-spots. Both visualisations do this by connecting profile...conference paper 2018
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Lu, Feng (author), Tintarev, N. (author)Diversity-based recommender systems aim to select a wide rangeof relevant content for users, but diversity needs for users withdifferent personalities are rarely studied. Similarly, research onpersonality-based recommender systems has primarily focused onthe ‘cold-start problem’; few previous works have investigated howpersonality influences...conference paper 2018