Publications related to A 3D Item Space Visualization for Presenting and Manipulating User Preferences in Collaborative Filtering
3D-Visualisierung zur Eingabe von Präferenzen in Empfehlungssystemen
Kunkel, J., Loepp, B., & Ziegler, J. (2015). Mensch Und Computer 2015 – Tagungsband, 123–132.
Kartenbasierte Produktraumdarstellung zur Erhöhung von Transparenz und Steuerbarkeit in Empfehlungssystemen
Kunkel, J., Feldkamp, T., & Ziegler, J. (2019). Mensch Und Computer 2019: Tagungsband.
LittleMissFits: Ein Game-With-A-Purpose zur Evaluierung subjektiver Verständlichkeit von latenten Faktoren in Empfehlungssystemen
Kunkel, J., Loepp, B., Dolff, E., & Ziegler, J. (2019). Mensch Und Computer 2019 – Workshopband, 49–56.
Visualizing Item Spaces to Increase Transparency and Control in Recommender Systems
Kunkel, J., & Ziegler, J. (2019). AI and HCI Workshop at CHI’19.
Understanding Latent Factors Using a GWAP
Kunkel, J., Loepp, B., & Ziegler, J. (2018). Proceedings of the Late-Breaking Results Track Part of the Twelfth ACM Conference on Recommender Systems (RecSys ’18).
Ein Online-Spiel zur Benennung latenter Faktoren in Empfehlungssystemen
Kunkel, J., Loepp, B., & Ziegler, J. (2018). Mensch Und Computer 2018 – Tagungsband.
User-centered recommender systems
Ziegler, J., & Loepp, B. (2023). In M. Augstein, E. Herder, & W. Wörndl (Eds.), Personalized Human-Computer Interaction (2nd ed., pp. 33–58). De Gruyter Oldenbourg.
Empfehlungssysteme
Ziegler, J., & Loepp, B. (2020). In T. Kollmann (Ed.), Handbuch Digitale Wirtschaft (pp. 717–741). Springer Gabler.
On User Awareness in Model-Based Collaborative Filtering Systems
Loepp, B., & Ziegler, J. (2017). Proceedings of the 1st Workshop on Awareness Interfaces and Interactions (AWARE ’17).
How Users Ride the Carousel: Exploring the Design of Multi-List Recommender Interfaces From a User Perspective
Loepp, B., & Ziegler, J. (2023). RecSys ’23: Proceedings of the 17th ACM Conference on Recommender Systems.
Towards Multi-Method Support for Product Search and Recommending
Kleemann, T., Loepp, B., & Ziegler, J. (2022). Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’22), 74–79.
NewsViz: Depicting and Controlling Preference Profiles Using Interactive Treemaps in News Recommender Systems
Kunkel, J., Schwenger, C., & Ziegler, J. (2020). UMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, 126–135.
Exploring Mental Models for Transparent and Controllable Recommender Systems: A Qualitative Study
Ngo, T. P., Kunkel, J., & Ziegler, J. (2020). UMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, 183–191.
Towards Interactive Recommending in Model-based Collaborative Filtering Systems
Loepp, B., & Ziegler, J. (2019). Proceedings of the 13th ACM Conference on Recommender Systems (RecSys ’19), 546–547.
Explaining Recommendations by Means of User Reviews
Donkers, T., Loepp, B., & Ziegler, J. (2018). Proceedings of the 1st Workshop on Explainable Smart Systems (ExSS ’18).
Sequential User-based Recurrent Neural Network Recommendations
Donkers, T., Loepp, B., & Ziegler, J. (2017). Proceedings of the 11th ACM Conference on Recommender Systems (RecSys ’17), 152–160.
Interactive Recommending: Framework, State of Research and Future Challenges
Loepp, B., Barbu, C.-M., & Ziegler, J. (2016). Proceedings of the 1st Workshop on Engineering Computer-Human Interaction in Recommender Systems (EnCHIReS ’16), 3–13.
Tag-Enhanced Collaborative Filtering for Increasing Transparency and Interactive Control
Donkers, T., Loepp, B., & Ziegler, J. (2016). Proceedings of the 24th Conference on User Modeling Adaptation and Personalization (UMAP ’16), 169–173.
Choice-based Preference Elicitation for Collaborative Filtering Recommender Systems
Loepp, B., Hussein, T., & Ziegler, J. (2014). Proceedings of the 32nd International Conference on Human Factors in Computing Systems (CHI ’14), 3085–3094.
Interaktive Empfehlungsgenerierung mit Hilfe latenter Produktfaktoren
Loepp, B., Hussein, T., & Ziegler, J. (2013). Mensch & Computer 2013 – Tagungsband, 17–26.
Interactive Methods for Model-based Collaborative Filtering Recommender Systems
Loepp, B. (2021). [PhD thesis, University of Duisburg-Essen].
On the Use of Feature-based Collaborative Explanations: An Empirical Comparison of Explanation Styles
Naveed, S., Loepp, B., & Ziegler, J. (2020). ExUM ’20: Proceedings of the International Workshop on Transparent Personalization Methods Based on Heterogeneous Personal Data, 226–232.
Measuring the Impact of Recommender Systems – A Position Paper on Item Consumption in User Studies
Loepp, B., & Ziegler, J. (2019). Proceedings of the 1st Workshop on Impact of Recommender Systems (ImpactRS ’19).
Recommending Running Routes: Framework and Demonstrator
Loepp, B., & Ziegler, J. (2018). Proceedings of the 2nd Second Workshop on Recommendation in Complex Scenarios (ComplexRec ’18), 26–29.
Towards Understanding Latent Factors and User Profiles by Enhancing Matrix Factorization with Tags
Donkers, T., Loepp, B., & Ziegler, J. (2016). Poster Proceedings of the 10th ACM Conference on Recommender Systems (RecSys ’16).
Merging Latent Factors and Tags to Increase Interactive Control of Recommendations
Donkers, T., Loepp, B., & Ziegler, J. (2015). Poster Proceedings of the 9th ACM Conference on Recommender Systems (RecSys ’15).
Merging Interactive Information Filtering and Recommender Algorithms: Model and Concept Demonstrator
Loepp, B., Herrmanny, K., & Ziegler, J. (2015). i-Com, 14(1), 5–17.
Blended Recommending: Integrating Interactive Information Filtering and Algorithmic Recommender Techniques
Loepp, B., Herrmanny, K., & Ziegler, J. (2015). Proceedings of the 33rd International Conference on Human Factors in Computing Systems (CHI ’15), 975–984.
How Users Ride the Carousel: Exploring the Design of Multi-List Recommender Interfaces From a User Perspective
Loepp, B., & Ziegler, J. (2023). In J. Zhang & L. Chen (Eds.), Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023 (pp. 1090–1095). Association for Computing Machinery, Inc.
Multi-list interfaces for recommender systems: Survey and future directions
Loepp, B. (2023). Frontiers in Big Data, 6.
An Interactive Hybrid Approach to Generate Explainable and Controllable Recommendations
Naveed, S. (2021). [PhD thesis, University of Duisburg-Essen].
Interactive Recommending with Tag-Enhanced Matrix Factorization (TagMF)
Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2019). International Journal of Human Computer Studies, 121, 21–41.
Ein kollaboratives Task-Management-System mit spielerischen Elementen
Kizina, A., Kunkel, J., & Ziegler, J. (2018). Mensch Und Computer 2018: Workshopband.
Eine Sandbox zur physisch-virtuellen Exploration von Ausgrabungsstätten
Biefang, K., Kunkel, J., Loepp, B., & Ziegler, J. (2017). Mensch Und Computer 2017 – Workshopband.
Enhancing an Interactive Recommendation System with Review-based Information Filtering
Feuerbach, J., Loepp, B., Barbu, C.-M., & Ziegler, J. (2017). Proceedings of the 4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS ’17), 1884, 2–9.
Evaluating the effectiveness of a memory aid system
Bayen, J. U., Dogangün, A., Grundgeiger, T., Haese, A., Stockmanns, G., & Ziegler, J. (2013). Gerontology : International Journal of Experimental and Clinical Gerontology, 59(1), 77–84.
Modeling User Interaction at the Convergence of Filtering Mechanisms, Recommender Algorithms and Advisory Components
Kleemann, T., Wagner, M., Loepp, B., & Ziegler, J. (2021). Mensch Und Computer 2021 – Tagungsband, 531–543.
Impact of Consuming Suggested Items on the Assessment of Recommendations in User Studies on Recommender Systems
Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2019). Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI ’19), 6201–6205.
Let Me Explain: Impact of Personal and Impersonal Explanations on Trust in Recommender Systems
Kunkel, J., Donkers, T., Michael, L., Barbu, C.-M., & Ziegler, J. (2019). Proceedings of the 37th International Conference on Human Factors in Computing Systems (CHI ’19), 487:1–487:12.
Impact of Item Consumption on Assessment of Recommendations in User Studies
Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2018). Proceedings of the 12th ACM Conference on Recommender Systems (RecSys ’18), 49–53.
Trust-Related Effects of Expertise and Similarity Cues in Human-Generated Recommendations
Kunkel, J., Donkers, T., Barbu, C.-M., & Ziegler, J. (2018). 2nd Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE).
MyMovieMixer: Ein hybrider Recommender mit visuellem Bedienkonzept
Herrmanny, K., Schering, S., Berger, R., Loepp, B., Günter, T., Hussein, T., & Ziegler, J. (2014). Mensch Und Computer 2014 – Tagungsband, 45–54.
An integrated approach for transparent, multi-level decision support in interactive recommender systems
Kleemann, T. (2024). [PhD thesis].
Explaining Recommendations through Conversations: Dialog Model and the Effects of Interface Type and Degree of Interactivity
Hernandez-Bocanegra, D. C., & Ziegler, J. (2023). ACM Transactions on Interactive Intelligent Systems (TiiS), 13(2).
A comparative study of item space visualizations for recommender systems
Kunkel, J., & Ziegler, J. (2023). International Journal of Human Computer Studies, 172.
Mental Models, Explanations, Visualizations: Promoting User-Centered Qualities in Recommender Systems
Kunkel, J. (2022). [PhD thesis, University of Duisburg-Essen].
Recommendations as Challenges: Estimating Required Effort and User Ability for Health Behavior Change Recommendations
Torkamaan, H., & Ziegler, J. (2022). 27th International Conference on Intelligent User Interfaces, 106–119.
Recommender Systems Alone Are Not Everything: Towards a Broader Perspective in the Evaluation of Recommender Systems
Loepp, B. (2022). PERSPECTIVES ’22: Proceedings of the 2nd Workshop on Perspectives on the Evaluation of Recommender Systems.
Development of an Instrument for Measuring Users’ Perception of Transparency in Recommender Systems
Hellmann, M., Hernandez Bocanegra, D., & Ziegler, J. (2022). In A. Smith-Renner & O. Amir (Eds.), Workshops at the International Conference on Intelligent User Interfaces (IUI) 2022: Proceedings of the IUI 2022 Workshops: APEx-UI, HAI-GEN, HEALTHI, HUMANIZE, TExSS, SOCIALIZE (Vol. 3124, pp. 156–165). RWTH Aachen.
Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics
Hernandez-Bocanegra, D. C., & Ziegler, J. (2020). i-Com: Journal of Interactive Media, 19(3), 181–200.
Mensch-Computer-Interaktion als zentrales Gebiet der Informatik: Bestandsaufnahme, Trends und Herausforderungen
Koch, M., Ziegler, J., Reuter, C., Schlegel, T., & Prilla, M. (2020). Informatik Spektrum, 43, 381–387.
Featuristic: An interactive hybrid system for generating explainable recommendations – Beyond system accuracy
Naveed, S., & Ziegler, J. (2020). Proceedings of the 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, 14–25.
Leveraging Arguments in User Reviews for Generating and Explaining Recommendations
Donkers, T., & Ziegler, J. (2020). Datenbank-Spektrum, 20(2), 181–187.
Challenges in User-Centered Engineering of AI-based Interactive Systems
Ziegler, J. (2019). In B. Weyers & J. Bowen (Eds.), Joint Proceedings HCI Engineering 2019 – Methods and Tools for Advanced Interactive Systems and Integration of Multiple Stakeholder Viewpoints co-located with 11th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2019) (Vol. 2503, pp. 51–55).
Feature-driven interactive recommendations and explanations with collaborative filtering approach
Naveed, S., & Ziegler, J. (2019). ComplexRec 2019: Proceedings of the Workshop on Recommendation in Complex Scenarios, 2449, 10–15.
To explain or not to explain: the effects of personal characteristics when explaining feature-based recommendations in different domains
Millecamp, M., Verbert, K., Naveed, S., & Ziegler, J. (2019). IntRS 2019: Proceedings of the 6th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, 2450, 10–18.
Hybreed: a software framework for developing context-aware hybrid recommender systems
Hussein, T., Linder, T., Gaulke, W., & Ziegler, J. (2014). User Modeling and User Adapted Interaction, 24(1), 121–174.