1. Psychological aspects in retrieval and recommendationMarkus Schedl, Elisabeth Lex, Marko Tkalčič, 2025, published scientific conference contribution abstract Abstract: Psychological processes play a critical role in shaping users’ inter- actions with information retrieval (IR) and recommender systems (RS). Therefore, understanding human cognition, decision-making, and emotions is vital to enable user-centric retrieval and recommendation systems. Vice versa, understanding whether these aspects are also present in the systems themselves (e.g., in training data, ranking models, or outputs), or even injecting them on purpose, can inform the development of psychology-inspired systems. The purpose of this tutorial is to provide its attendees with an introduction to psychological concepts that are important in the ecosystem of search, retrieval, and recommendation, in particular, cognitive architectures, cognitive effects and biases, as well as personality and affect. Leveraging corresponding models allows its audience to build or refine psychology-informed IR and RS technology. The interdisciplinary tutorial requires intermediate expertise in terms of IR and RS, while we do not assume knowledge in psychology.
Keywords: recommender systems, emotions, personality
Published in RUP: 08.04.2026; Views: 43; Downloads: 2
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7. Recommending videos in cold start with automatic visual tagsMehdi Elahi, Farshad B. Moghaddam, Reza Hosseini, Mohammad Hossein Rimaz, Nabil El Ioini, Marko Tkalčič, Christoph Trattner, Tammam Tillo, 2021, published scientific conference contribution Keywords: recommender systems, visual tags, visual features, cold start
Published in RUP: 16.07.2021; Views: 2714; Downloads: 31
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