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On-demand Personalized Explanation for Transparent Recommendation.

, , , , , , , and . UMAP (Adjunct Publication), page 246-252. ACM, (2021)

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Validation of the EDUSS Framework for Self-Actualization Based on Transparent User Models: A Qualitative Study., , , , , and . UMAP (Adjunct Publication), page 229-238. ACM, (2023)How to Design Effective Learning Analytics Indicators? A Human-Centered Design Approach., , , , , , and . EC-TEL, volume 12315 of Lecture Notes in Computer Science, page 303-317. Springer, (2020)What if Interactive Explanation in a Scientific Literature Recommender System., , , , , and . IntRS@RecSys, volume 3222 of CEUR Workshop Proceedings, page 104-121. CEUR-WS.org, (2022)Input or Output: Effects of Explanation Focus on the Perception of Explainable Recommendation with Varying Level of Details., , , , , , , , , and . IntRS@RecSys, volume 2948 of CEUR Workshop Proceedings, page 55-72. CEUR-WS.org, (2021)SIMT: A Semantic Interest Modeling Toolkit., , , , , and . UMAP (Adjunct Publication), page 75-78. ACM, (2021)Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System., , , , , , and . Inf., 14 (7): 401 (2023)Interactive Visualizations of Transparent User Models for Self-Actualization: A Human-Centered Design Approach., , , , and . Multimodal Technol. Interact., 6 (6): 42 (2022)On-demand Personalized Explanation for Transparent Recommendation., , , , , , , and . UMAP (Adjunct Publication), page 246-252. ACM, (2021)Explaining User Models with Different Levels of Detail for Transparent Recommendation: A User Study., , , , , , and . UMAP (Adjunct Publication), page 175-183. ACM, (2022)Is More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System., , , , , , and . UMAP, page 254-264. ACM, (2022)