Iskanje po repozitoriju

Towards a client-side HATEOAS-based recommender system : final project paper
Iuliia Kudiaeva, 2026, diplomsko delo

Ključne besede: recommender systems, privacy-preserving recommender systems, clientside recommendation, HATEOAS, content-based filtering
Objavljeno v RUP: 27.04.2026; Ogledov: 173; Prenosov: 7
Celotno besedilo (315,98 KB)

Psychological aspects in retrieval and recommendation
Markus Schedl, Elisabeth Lex, Marko Tkalčič, 2025, objavljeni povzetek znanstvenega prispevka na konferenci

Opis: 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.
Ključne besede: recommender systems, emotions, personality
Objavljeno v RUP: 08.04.2026; Ogledov: 219; Prenosov: 7
Celotno besedilo (954,00 KB)
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Music and myth : the relationship between music preference and unverified beliefs
Elena Spirova, 2024, magistrsko delo

Ključne besede: predictive analysis, recommender systems, personality, beliefs, music
Objavljeno v RUP: 15.09.2024; Ogledov: 1681; Prenosov: 44
Celotno besedilo (482,08 KB)

Analiza pomena značilk za napoved ocen filmov : zaključna naloga
Nadeen Al Hawamdeh, 2023, diplomsko delo

Ključne besede: computer science, recommender systems, feature importance, ablation, machine learning
Objavljeno v RUP: 10.10.2023; Ogledov: 3026; Prenosov: 27
Celotno besedilo (368,98 KB)

Recommending videos in cold start with automatic visual tags
Mehdi Elahi, Farshad B. Moghaddam, Reza Hosseini, Mohammad Hossein Rimaz, Nabil El Ioini, Marko Tkalčič, Christoph Trattner, Tammam Tillo, 2021, objavljeni znanstveni prispevek na konferenci

Ključne besede: recommender systems, visual tags, visual features, cold start
Objavljeno v RUP: 16.07.2021; Ogledov: 2831; Prenosov: 32
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