personalization

The Role of Human-Centered AI in User Modeling, Adaptation, and Personalization—Models, Frameworks, and Paradigms

Helma Torkamaan, Mohammad Tahaei, Stefan Buijsman, Ziang Xiao, Daricia Wilkinson, Bart P. Knijnenburg Abstract This chapter explores the principles and frameworks of human-centered artificial intelligence (AI), specifically focusing on user modeling, adaptation, and personalization. It introduces a four-dimensional framework comprising paradigms, actors, values, and levels of realization that should be considered in the design of […]

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How can they know that? A study of factors affecting the creepiness of recommendations

Helma Torkamaan, , Catalin-Mihai Barbu, Jürgen Ziegler Abstract Recommender systems (RS) often use implicit user preferences extracted from behavioral and contextual data, in addition to traditional rating-based preference elicitation, to increase the quality and accuracy of personalized recommendations. However, these approaches may harm user experience by causing mixed emotions, such as fear, anxiety, surprise, discomfort,

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