Recommending tags with a model of human categorization. - Paul Seitlinger; Dominik Kowald; Christoph Trattner; Tobias Ley (CIKM, 2013)

The Social Semantic Server - A Framework to Provide Services on Social Semantic Network Data. - Dominik Kowald; Sebastian Dennerlein; Dieter Theiler; Simon Walk; Christoph Trattner (I-SEMANTICS (Posters & Demos), 2013)

Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context. - Dominik Kowald; Simone Kopeinik; Paul Seitlinger; Tobias Ley; Dietrich Albert; Christoph Trattner (MSM/MUSE, 2013)

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender. - Dominik Kowald; Paul Seitlinger; Simone Kopeinik; Tobias Ley; Christoph Trattner (MSM/MUSE, 2013)

Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces. - Emanuel Lacic; Dominik Kowald; Lukas Eberhard; Christoph Trattner; Denis Parra; Leandro Balby Marinho (MSM/MUSE, 2013)

TagRec: towards a standardized tag recommender benchmarking framework. - Dominik Kowald; Emanuel Lacic; Christoph Trattner (HT, 2014)

Recommending Items in Social Tagging Systems Using Tag and Time Informations. - Emanuel Lacic; Dominik Kowald; Paul Seitlinger; Christoph Trattner; Denis Parra (HT (Doctoral Consortium / Late-breaking Results / Workshops), 2014)

SocRecM: a scalable social recommender engine for online marketplaces. - Emanuel Lacic; Dominik Kowald; Christoph Trattner (HT, 2014)

Long time no see: the probability of reusing tags as a function of frequency and recency. - Dominik Kowald; Paul Seitlinger; Christoph Trattner; Tobias Ley (WWW (Companion Volume), 2014)

Towards a scalable social recommender engine for online marketplaces: the case of apache solr. - Emanuel Lacic; Dominik Kowald; Denis Parra; Martin Kahr; Christoph Trattner (WWW (Companion Volume), 2014)

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender. - Dominik Kowald; Paul Seitlinger; Christoph Trattner; Tobias Ley (CoRR, 2014)

Utilizing Online Social Network and Location-Based Data to Recommend Items in an Online Marketplace. - Emanuel Lacic; Dominik Kowald; Lukas Eberhard; Christoph Trattner; Denis Parra; Leandro Balby Marinho (CoRR, 2014)

Recommending Items in Social Tagging Systems Using Tag and Time Information. - Emanuel Lacic; Dominik Kowald; Paul Seitlinger; Christoph Trattner; Denis Parra (CoRR, 2014)

The social semantic server: a flexible framework to support informal learning at the workplace. - Sebastian Dennerlein; Dominik Kowald; Elisabeth Lex; Dieter Theiler; Emanuel Lacic; Tobias Ley (I-KNOW, 2015)

Smart booking without looking: providing hotel recommendations in the TripRebel portal. - Matthias Traub; Dominik Kowald; Emanuel Lacic; Pepijn Schoen; Gernot Supp; Elisabeth Lex (I-KNOW, 2015)

Evaluating Tag Recommender Algorithms in Real-World Folksonomies: A Comparative Study. - Dominik Kowald; Elisabeth Lex (RecSys, 2015)

Tackling Cold-Start Users in Recommender Systems with Indoor Positioning Systems. - Emanuel Lacic; Dominik Kowald; Matthias Traub; Granit Luzhnica; Jörg Simon; Elisabeth Lex (RecSys Posters, 2015)

Modeling Cognitive Processes in Social Tagging to Improve Tag Recommendations. - Dominik Kowald (WWW (Companion Volume), 2015)

Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics. - Paul Seitlinger; Dominik Kowald; Simone Kopeinik; Ilire Hasani-Mavriqi; Elisabeth Lex; Tobias Ley (WWW (Companion Volume), 2015)

TagRec: towards a toolkit for reproducible evaluation and development of tag-based recommender algorithms. - Christoph Trattner; Dominik Kowald; Emanuel Lacic (SIGWEB Newsl., 2015)

Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL. - Simone Kopeinik; Dominik Kowald; Elisabeth Lex (EC-TEL, 2016)

The Influence of Frequency, Recency and Semantic Context on the Reuse of Tags in Social Tagging Systems. - Dominik Kowald; Elisabeth Lex (HT, 2016)

High Enough?: Explaining and Predicting Traveler Satisfaction Using Airline Reviews. - Emanuel Lacic; Dominik Kowald; Elisabeth Lex (HT, 2016)

High Enough? Explaining and Predicting Traveler Satisfaction Using Airline Review. - Emanuel Lacic; Dominik Kowald; Elisabeth Lex (CoRR, 2016)

Going beyond your Personal Learning Network, Using Recommendations and Trust through a Multimedia Question-Answering Service for Decision-support: a Case Study in the Healthcare. - Patricia Santos 001; Elisabeth Lex; Sebastian Dennerlein; Dieter Theiler; John Cook; Tamsin Treasure-Jones; Debbie Holley; Micky Kerr; Graham Attwell; Dominik Kowald (J. Univers. Comput. Sci., 2016)

Modeling Activation Processes in Human Memory to Predict the Use of Tags in Social Bookmarking Systems. - Christoph Trattner; Dominik Kowald; Paul Seitlinger; Tobias Ley; Simone Kopeinik (J. Web Sci., 2016)

AFEL: Towards Measuring Online Activities Contributions to Self-directed Learning. - Mathieu d'Aquin; Alessandro Adamou; Stefan Dietze; Besnik Fetahu; Ujwal Gadiraju; Ilire Hasani-Mavriqi; Peter Holtz; Joachim Kimmerle; Dominik Kowald; Elisabeth Lex; Susana López-Sola; Ricardo Alonso Maturana; et al. (ARTEL@EC-TEL, 2017)

Tailoring Recommendations for a Multi-Domain Environment. - Emanuel Lacic; Dominik Kowald; Elisabeth Lex (RecSysKTL, 2017)

The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems. - Dominik Kowald; Simone Kopeinik; Elisabeth Lex (UMAP (Adjunct Publication), 2017)

Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. - Dominik Kowald; Subhash Chandra Pujari; Elisabeth Lex (WWW, 2017)

Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendations. - Emanuel Lacic; Dominik Kowald; Markus Reiter-Haas; Valentin Slawicek; Elisabeth Lex (CoRR, 2017)

Improving Collaborative Filtering Using a Cognitive Model of Human Category Learning. - Simone Kopeinik; Dominik Kowald; Ilire Hasani-Mavriqi; Elisabeth Lex (J. Web Sci., 2017)

Modeling Activation Processes in Human Memory to Improve Tag Recommendations. - Dominik Kowald (SIGIR Forum, 2017)

AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments. - Dominik Kowald; Emanuel Lacic; Dieter Theiler; Elisabeth Lex (CIKM Workshops, 2018)

Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations. - Emanuel Lacic; Dominik Kowald; Elisabeth Lex (CIKM Workshops, 2018)

Simulation-based Co-Creation of Algorithms. - Sebastian Dennerlein; Dominik Kowald; Viktoria Pammer-Schindler; Elisabeth Lex; Tobias Ley (CC-TEL/TACKLE@EC-TEL, 2018)

Analytics for Everyday Learning from two Perspectives: Knowledge Workers and Teachers. - Angela Fessl; Dominik Kowald; Susana López-Sola; Ana Moreno; Ricardo Alonso Maturana; Stefan Thalmann (AFEL@EC-TEL, 2018)

Trust-based collaborative filtering: tackling the cold start problem using regular equivalence. - Tomislav Duricic; Emanuel Lacic; Dominik Kowald; Elisabeth Lex (RecSys, 2018)

The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study. - Dominik Kowald; Paul Seitlinger; Tobias Ley; Elisabeth Lex (WWW (Companion Volume), 2018)

AFEL - Analytics for Everyday Learning. - Mathieu d'Aquin; Dominik Kowald; Angela Fessl; Elisabeth Lex; Stefan Thalmann (WWW (Companion Volume), 2018)

Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms. - Dominik Kowald; Elisabeth Lex (CoRR, 2018)

Studying Confirmation Bias in Hashtag Usage on Twitter. - Dominik Kowald; Elisabeth Lex (CoRR, 2018)

Mitigating Confirmation Bias on Twitter by Recommending Opposing Views. - Elisabeth Lex; Mario Wagner; Dominik Kowald (CoRR, 2018)

Balancing the Fluency-Consistency Tradeoff in Collaborative Information Search with a Recommender Approach. - Paul Seitlinger; Tobias Ley; Dominik Kowald; Dieter Theiler; Ilire Hasani-Mavriqi; Sebastian Dennerlein; Elisabeth Lex; Dietrich Albert (Int. J. Hum. Comput. Interact., 2018)

A Real-Life School Study of Confirmation Bias and Polarisation in Information Behaviour. - Simone Kopeinik; Elisabeth Lex; Dominik Kowald; Dietrich Albert; Paul Seitlinger (EC-TEL, 2019)

The Impact of Time on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. - Elisabeth Lex; Dominik Kowald (GI-Jahrestagung, 2019)

Modeling Artist Preferences of Users with Different Music Consumption Patterns for Fair Music Recommendations. - Dominik Kowald; Elisabeth Lex; Markus Schedl (CoRR, 2019)

Exploiting weak ties in trust-based recommender systems using regular equivalence. - Tomislav Duricic; Emanuel Lacic; Dominik Kowald; Elisabeth Lex (CoRR, 2019)

Using the Open Meta Kaggle Dataset to Evaluate Tripartite Recommendations in Data Markets. - Dominik Kowald; Matthias Traub; Dieter Theiler; Heimo Gursch; Emanuel Lacic; Stefanie N. Lindstaedt; Roman Kern; Elisabeth Lex (CoRR, 2019)

Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric. - Emanuel Lacic; Dominik Kowald; Dieter Theiler; Matthias Traub; Lucky Kuffer; Stefanie N. Lindstaedt; Elisabeth Lex (CoRR, 2019)

An Infrastructure for Workplace Learning Analytics: Tracing Knowledge Creation with the Social Semantic Server. - Adolfo Ruiz-Calleja; Sebastian Dennerlein; Dominik Kowald; Dieter Theiler; Elisabeth Lex; Tobias Ley (J. Learn. Anal., 2019)

The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. - Dominik Kowald; Markus Schedl; Elisabeth Lex (ECIR (2), 2020)

Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering. - Tomislav Duricic; Hussain Hussain; Emanuel Lacic; Dominik Kowald; Denis Helic; Elisabeth Lex (ISMIS, 2020)

Slow is good: the effect of diligence on student performance in the case of an adaptive learning system for health literacy. - Leon Fadljevic; Katharina Maitz; Dominik Kowald; Viktoria Pammer-Schindler; Barbara Gasteiger-Klicpera (LAK, 2020)

Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations. - Dominik Kowald; Elisabeth Lex; Markus Schedl (CoRR, 2020)

Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes. - Markus Schedl; Christine Bauer 001; Wolfgang Reisinger; Dominik Kowald; Elisabeth Lex (Frontiers Artif. Intell., 2020)

Modeling Popularity and Temporal Drift of Music Genre Preferences. - Elisabeth Lex; Dominik Kowald; Markus Schedl (Trans. Int. Soc. Music. Inf. Retr., 2020)

Using autoencoders for session-based job recommendations. - Emanuel Lacic; Markus Reiter-Haas; Dominik Kowald; Manoj Reddy Dareddy; Junghoo Cho; Elisabeth Lex (User Model. User Adapt. Interact., 2020)

My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. - Tomislav Duricic; Dominik Kowald; Markus Schedl; Elisabeth Lex (ASONAM, 2021)

Robustness of Meta Matrix Factorization Against Strict Privacy Constraints. - Peter Müllner; Dominik Kowald; Elisabeth Lex (ECIR (2), 2021)

Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? - Oleg Lesota; Alessandro B. Melchiorre; Navid Rekabsaz; Stefan Brandl; Dominik Kowald; Elisabeth Lex; Markus Schedl (RecSys, 2021)

Position Paper on Simulating Privacy Dynamics in Recommender Systems. - Peter Müllner; Elisabeth Lex; Dominik Kowald (CoRR, 2021)

Support the underground: characteristics of beyond-mainstream music listeners. - Dominik Kowald; Peter Müllner; Eva Zangerle; Christine Bauer 001; Markus Schedl; Elisabeth Lex (EPJ Data Sci., 2021)

Psychology-informed Recommender Systems. - Elisabeth Lex; Dominik Kowald; Paul Seitlinger; Thi Ngoc Trang Tran; Alexander Felfernig; Markus Schedl (Found. Trends Inf. Retr., 2021)

Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems. - Dominik Kowald; Emanuel Lacic (BIAS, 2022)

Towards employing recommender systems for supporting data and algorithm sharing. - Peter Müllner; Stefan Schmerda; Dieter Theiler; Stefanie N. Lindstaedt; Dominik Kowald (DE@CoNEXT, 2022)

What Drives Readership? An Online Study on User Interface Types and Popularity Bias Mitigation in News Article Recommendations. - Emanuel Lacic; Leon Fadljevic; Franz Weissenboeck; Stefanie N. Lindstaedt; Dominik Kowald (ECIR (2), 2022)

Recommendations in a Multi-Domain Setting: Adapting for Customization, Scalability and Real-Time Performance. - Emanuel Lacic; Dominik Kowald (CoRR, 2022)

ReuseKNN: Neighborhood Reuse for Privacy-Aware Recommendations. - Peter Müllner; Markus Schedl; Elisabeth Lex; Dominik Kowald (CoRR, 2022)

Long-term dynamics of fairness: understanding the impact of data-driven targeted help on job seekers. - Sebastian Scher; Simone Kopeinik; Andreas Trügler; Dominik Kowald (CoRR, 2022)

A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. - Dominik Kowald; Gregor Mayr; Markus Schedl; Elisabeth Lex (BIAS, 2023)

Uptrendz: API-Centric Real-Time Recommendations in Multi-domain Settings. - Emanuel Lacic; Tomislav Duricic; Leon Fadljevic; Dieter Theiler; Dominik Kowald (ECIR (3), 2023)

Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. - Marta Moscati; Christian Wallmann; Markus Reiter-Haas; Dominik Kowald; Elisabeth Lex; Markus Schedl (RecSys, 2023)

A conceptual model for leaving the data-centric approach in machine learning. - Sebastian Scher; Bernhard C. Geiger; Simone Kopeinik; Andreas Trügler; Dominik Kowald (CoRR, 2023)

Reproducibility in Machine Learning-Driven Research. - Harald Semmelrock; Simone Kopeinik; Dieter Theiler; Tony Ross-Hellauer; Dominik Kowald (CoRR, 2023)

Take the aTrain. Introducing an Interface for the Accessible Transcription of Interviews. - Armin Haberl; Jürgen Fleiß; Dominik Kowald; Stefan Thalmann (CoRR, 2023)

Files for Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. - Marta Moscati; Christian Wallmann; Markus Reiter-Haas; Dominik Kowald; Elisabeth Lex; Markus Schedl (Zenodo, 2023)

ReuseKNN: Neighborhood Reuse for Differentially Private KNN-Based Recommendations. - Peter Müllner; Elisabeth Lex; Markus Schedl; Dominik Kowald (ACM Trans. Intell. Syst. Technol., 2023)

AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments. - Tomislav Duricic; Peter Müllner; Nicole Weidinger; Neven A. M. ElSayed; Dominik Kowald; Eduardo E. Veas (ECAI, 2024)

The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. - Peter Müllner; Elisabeth Lex; Markus Schedl; Dominik Kowald (ECIR (4), 2024)

Black Box or Open Science? Assessing Reproducibility-Related Documentation in AI Research. - Florian Koenigstorfer; Armin Haberl; Dominik Kowald; Tony Ross-Hellauer; Stefan Thalmann (HICSS, 2024)

Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the Digital Archive Monasterium.net. - Florian Atzenhofer-Baumgartner; Bernhard C. Geiger; Georg Vogeler; Dominik Kowald (NORMalize@RecSys, 2024)

Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. - Gustavo Escobedo; Marta Moscati; Peter Muellner; Simone Kopeinik; Dominik Kowald; Elisabeth Lex; Markus Schedl (ECML/PKDD (7), 2024)

Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems. - Oleg Lesota; Jonas Geiger; Max Walder; Dominik Kowald; Markus Schedl (RecSys, 2024)

Transparency, Privacy, and Fairness in Recommender Systems. - Dominik Kowald (CoRR, 2024)

Challenges in Implementing a Recommender System for Historical Research in the Humanities. - Florian Atzenhofer-Baumgartner; Bernhard C. Geiger; Christoph Trattner; Georg Vogeler; Dominik Kowald (CoRR, 2024)

Beyond-accuracy: a review on diversity, serendipity, and fairness in recommender systems based on graph neural networks. - Tomislav Duricic; Dominik Kowald; Emanuel Lacic; Elisabeth Lex (Frontiers Big Data, 2024)

Establishing and evaluating trustworthy AI: overview and research challenges. - Dominik Kowald; Sebastian Scher; Viktoria Pammer-Schindler; Peter Müllner; Kerstin Waxnegger; Lea Demelius; Angela Fessl; Maximilian Toller; Inti Gabriel Mendoza Estrada; Ilija Simic; Vedran Sabol; Andreas Trügler; et al. (Frontiers Big Data, 2024)

Editorial: Reviews in recommender systems: 2022. - Dominik Kowald; Deqing Yang; Emanuel Lacic (Frontiers Big Data, 2024)

Differential privacy in collaborative filtering recommender systems: a review. - Peter Müllner; Elisabeth Lex; Markus Schedl; Dominik Kowald (Frontiers Big Data, 2024)

LFM User Groups Implicit Feedback. - Peter Müllner; Elisabeth Lex; Markus Schedl; Dominik Kowald (Zenodo, 2024)

AI Certification and Assessment Catalogues: Practical Use and Challenges in the Context of the European AI Act. - Gregor Autischer; Kerstin Waxnegger; Dominik Kowald (EWAF, 2025)

Investigating Popularity Bias Amplification in Recommender Systems Employed in the Entertainment Domain. - Dominik Kowald (EWAF, 2025)

Hybrid Personalization Using Declarative and Procedural Memory Modules of the Cognitive Architecture ACT-R. - Kevin Innerebner; Dominik Kowald; Markus Schedl; Elisabeth Lex (UMAP (Adjunct Publication), 2025)

Hybrid AI for Human-Centric Personalization (HyPer). - Elisabeth Lex; Kevin Innerebner; Marko Tkalcic; Dominik Kowald; Markus Schedl (UMAP (Adjunct Publication), 2025)

Reproducibility in machine-learning-based research: Overview, barriers, and drivers. - Harald Semmelrock; Tony Ross-Hellauer; Simone Kopeinik; Dieter Theiler; Armin Haberl; Stefan Thalmann; Dominik Kowald (AI Mag., 2025)

De-centering the (Traditional) user: Multistakeholder evaluation of recommender systems. - Robin Burke; Gediminas Adomavicius; Toine Bogers; Tommaso Di Noia; Dominik Kowald; Julia Neidhardt; Özlem Özgöbek; Maria Soledad Pera; Nava Tintarev; Jürgen Ziegler 001 (Int. J. Hum. Comput. Stud., 2025)

Practical Application and Limitations of AI Certification Catalogues in the Light of the AI Act. - Gregor Autischer; Kerstin Waxnegger; Dominik Kowald (CoRR, 2025)

Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations. - Andrea Forster; Simone Kopeinik; Denis Helic; Stefan Thalmann; Dominik Kowald (CoRR, 2025)

A Multistakeholder Approach to Value-Driven Co-Design of Recommender System Evaluation Metrics in Digital Archives. - Florian Atzenhofer-Baumgartner; Georg Vogeler; Dominik Kowald (CoRR, 2025)

Impacts of Mainstream-Driven Algorithms on Recommendations for Children Across Domains: A Reproducibility Study. - Robin Ungruh; Alejandro Bellogín; Dominik Kowald; Maria Soledad Pera (CoRR, 2025)