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Dominik Kowald

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affiliation: Graz University of Technology, Austria

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2024
[j16]
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Tomislav Duricic, Dominik Kowald, Emanuel Lacic, Elisabeth Lex:
Beyond-accuracy: a review on diversity, serendipity, and fairness in recommender systems based on graph neural networks. Frontiers Big Data 6 (2024)
[j15]
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Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
Differential privacy in collaborative filtering recommender systems: a review. Frontiers Big Data 6 (2024)
[j14]
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Dominik Kowald, Deqing Yang, Emanuel Lacic:
Editorial: Reviews in recommender systems: 2022. Frontiers Big Data 7 (2024)
2023
[j13]
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Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
ReuseKNN: Neighborhood Reuse for Differentially Private KNN-Based Recommendations. ACM Trans. Intell. Syst. Technol. 14(5): 80:1-80:29 (2023)
2021
[j12]
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Dominik Kowald, Peter Müllner, Eva Zangerle, Christine Bauer, Markus Schedl, Elisabeth Lex:
Support the underground: characteristics of beyond-mainstream music listeners. EPJ Data Sci. 10(1): 14 (2021)
[j11]
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Elisabeth Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, Alexander Felfernig, Markus Schedl:
Psychology-informed Recommender Systems. Found. Trends Inf. Retr. 15(2): 134-242 (2021)
2020
[j10]
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Markus Schedl, Christine Bauer, Wolfgang Reisinger, Dominik Kowald, Elisabeth Lex:
Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes. Frontiers Artif. Intell. 3: 508725 (2020)
[j9]
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Elisabeth Lex, Dominik Kowald, Markus Schedl:
Modeling Popularity and Temporal Drift of Music Genre Preferences. Trans. Int. Soc. Music. Inf. Retr. 3(1): 17-30 (2020)
[j8]
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Emanuel Lacic, Markus Reiter-Haas, Dominik Kowald, Manoj Reddy Dareddy, Junghoo Cho, Elisabeth Lex:
Using autoencoders for session-based job recommendations. User Model. User Adapt. Interact. 30(4): 617-658 (2020)
2019
[j7]
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Adolfo Ruiz-Calleja, Sebastian Dennerlein, Dominik Kowald, Dieter Theiler, Elisabeth Lex, Tobias Ley:
An Infrastructure for Workplace Learning Analytics: Tracing Knowledge Creation with the Social Semantic Server. J. Learn. Anal. 6(2) (2019)
2018
[j6]
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Paul Seitlinger, Tobias Ley, Dominik Kowald, Dieter Theiler, Ilire Hasani-Mavriqi, Sebastian Dennerlein, Elisabeth Lex, Dietrich Albert:
Balancing the Fluency-Consistency Tradeoff in Collaborative Information Search with a Recommender Approach. Int. J. Hum. Comput. Interact. 34(6): 557-575 (2018)
2017
[j5]
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Simone Kopeinik, Dominik Kowald, Ilire Hasani-Mavriqi, Elisabeth Lex:
Improving Collaborative Filtering Using a Cognitive Model of Human Category Learning. J. Web Sci. 2(4): 45-61 (2017)
[j4]
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Dominik Kowald:
Modeling Activation Processes in Human Memory to Improve Tag Recommendations. SIGIR Forum 51(3): 166 (2017)
2016
[j3]
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Patricia Santos, Elisabeth Lex, Sebastian Dennerlein, Dieter Theiler, John Cook, Tamsin Treasure-Jones, Debbie Holley, Micky Kerr, Graham Attwell, Dominik Kowald:
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. J. Univers. Comput. Sci. 22(3): 340-359 (2016)
[j2]
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Christoph Trattner, Dominik Kowald, Paul Seitlinger, Tobias Ley, Simone Kopeinik:
Modeling Activation Processes in Human Memory to Predict the Use of Tags in Social Bookmarking Systems. J. Web Sci. 2(1): 1-16 (2016)
2015
[j1]
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Christoph Trattner, Dominik Kowald, Emanuel Lacic:
TagRec: towards a toolkit for reproducible evaluation and development of tag-based recommender algorithms. SIGWEB Newsl. 2015(Winter): 3:1-3:10 (2015)

Conference and Workshop Papers

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2024
[c47]
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Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. ECIR (4) 2024: 466-482
[c46]
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Florian Koenigstorfer, Armin Haberl, Dominik Kowald, Tony Ross-Hellauer, Stefan Thalmann:
Black Box or Open Science? Assessing Reproducibility-Related Documentation in AI Research. HICSS 2024: 682-691
[c45]
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Gustavo Escobedo, Marta Moscati, Peter Muellner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. ECML/PKDD (7) 2024: 349-365
2023
[c44]
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  - conf/bias/KowaldMSL23
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Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. BIAS 2023: 1-16
[c43]
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Emanuel Lacic, Tomislav Duricic, Leon Fadljevic, Dieter Theiler, Dominik Kowald:
Uptrendz: API-Centric Real-Time Recommendations in Multi-domain Settings. ECIR (3) 2023: 255-261
[c42]
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Marta Moscati, Christian Wallmann, Markus Reiter-Haas, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. RecSys 2023: 840-847
2022
[c41]
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Dominik Kowald, Emanuel Lacic:
Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems. BIAS 2022: 1-11
[c40]
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Peter Müllner, Stefan Schmerda, Dieter Theiler, Stefanie N. Lindstaedt, Dominik Kowald:
Towards employing recommender systems for supporting data and algorithm sharing. DE@CoNEXT 2022: 8-14
[c39]
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Emanuel Lacic, Leon Fadljevic, Franz Weissenboeck, Stefanie N. Lindstaedt, Dominik Kowald:
What Drives Readership? An Online Study on User Interface Types and Popularity Bias Mitigation in News Article Recommendations. ECIR (2) 2022: 172-179
2021
[c38]
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Tomislav Duricic, Dominik Kowald, Markus Schedl, Elisabeth Lex:
My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. ASONAM 2021: 447-454
[c37]
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Peter Müllner, Dominik Kowald, Elisabeth Lex:
Robustness of Meta Matrix Factorization Against Strict Privacy Constraints. ECIR (2) 2021: 107-119
[c36]
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Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? RecSys 2021: 601-606
2020
[c35]
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Dominik Kowald, Markus Schedl, Elisabeth Lex:
The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. ECIR (2) 2020: 35-42
[c34]
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  - conf/ismis/DuricicHLKHL20
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Tomislav Duricic, Hussain Hussain, Emanuel Lacic, Dominik Kowald, Denis Helic, Elisabeth Lex:
Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering. ISMIS 2020: 181-191
[c33]
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Leon Fadljevic, Katharina Maitz, Dominik Kowald, Viktoria Pammer-Schindler, Barbara Gasteiger-Klicpera:
Slow is good: the effect of diligence on student performance in the case of an adaptive learning system for health literacy. LAK 2020: 112-117
2019
[c32]
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Simone Kopeinik, Elisabeth Lex, Dominik Kowald, Dietrich Albert, Paul Seitlinger:
A Real-Life School Study of Confirmation Bias and Polarisation in Information Behaviour. EC-TEL 2019: 409-422
[c31]
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Elisabeth Lex, Dominik Kowald:
The Impact of Time on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. GI-Jahrestagung 2019: 285-286
2018
[c30]
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Dominik Kowald, Emanuel Lacic, Dieter Theiler, Elisabeth Lex:
AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments. CIKM Workshops 2018
[c29]
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Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations. CIKM Workshops 2018
[c28]
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Sebastian Dennerlein, Dominik Kowald, Viktoria Pammer-Schindler, Elisabeth Lex, Tobias Ley:
Simulation-based Co-Creation of Algorithms. CC-TEL/TACKLE@EC-TEL 2018
[c27]
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Angela Fessl, Dominik Kowald, Susana López-Sola, Ana Moreno, Ricardo Alonso Maturana, Stefan Thalmann:
Analytics for Everyday Learning from two Perspectives: Knowledge Workers and Teachers. AFEL@EC-TEL 2018
[c26]
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Tomislav Duricic, Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
Trust-based collaborative filtering: tackling the cold start problem using regular equivalence. RecSys 2018: 446-450
[c25]
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Dominik Kowald, Paul Seitlinger, Tobias Ley, Elisabeth Lex:
The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study. WWW (Companion Volume) 2018: 1-2
[c24]
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Mathieu d'Aquin, Dominik Kowald, Angela Fessl, Elisabeth Lex, Stefan Thalmann:
AFEL - Analytics for Everyday Learning. WWW (Companion Volume) 2018: 439-440
2017
[c23]
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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, Vedran Sabol, Pinelopi Troullinou, Eduardo E. Veas:
AFEL: Towards Measuring Online Activities Contributions to Self-directed Learning. ARTEL@EC-TEL 2017
[c22]
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Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
Tailoring Recommendations for a Multi-Domain Environment. RecSysKTL 2017: 42-45
[c21]
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Dominik Kowald, Simone Kopeinik, Elisabeth Lex:
The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems. UMAP (Adjunct Publication) 2017: 23-28
[c20]
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Dominik Kowald, Subhash Chandra Pujari, Elisabeth Lex:
Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. WWW 2017: 1401-1410
2016
[c19]
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Simone Kopeinik, Dominik Kowald, Elisabeth Lex:
Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL. EC-TEL 2016: 124-138
[c18]
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Dominik Kowald, Elisabeth Lex:
The Influence of Frequency, Recency and Semantic Context on the Reuse of Tags in Social Tagging Systems. HT 2016: 237-242
[c17]
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Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
High Enough?: Explaining and Predicting Traveler Satisfaction Using Airline Reviews. HT 2016: 249-254
2015
[c16]
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  - conf/iknow/DennerleinKLTLL15
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Sebastian Dennerlein, Dominik Kowald, Elisabeth Lex, Dieter Theiler, Emanuel Lacic, Tobias Ley:
The social semantic server: a flexible framework to support informal learning at the workplace. I-KNOW 2015: 26:1-26:8
[c15]
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Matthias Traub, Dominik Kowald, Emanuel Lacic, Pepijn Schoen, Gernot Supp, Elisabeth Lex:
Smart booking without looking: providing hotel recommendations in the TripRebel portal. I-KNOW 2015: 50:1-50:4
[c14]
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Dominik Kowald, Elisabeth Lex:
Evaluating Tag Recommender Algorithms in Real-World Folksonomies: A Comparative Study. RecSys 2015: 265-268
[c13]
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Emanuel Lacic, Dominik Kowald, Matthias Traub, Granit Luzhnica, Jörg Simon, Elisabeth Lex:
Tackling Cold-Start Users in Recommender Systems with Indoor Positioning Systems. RecSys Posters 2015
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Paul Seitlinger, Dominik Kowald, Simone Kopeinik, Ilire Hasani-Mavriqi, Elisabeth Lex, Tobias Ley:
Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics. WWW (Companion Volume) 2015: 339-345
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Dominik Kowald:
Modeling Cognitive Processes in Social Tagging to Improve Tag Recommendations. WWW (Companion Volume) 2015: 505-509
2014
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Dominik Kowald, Emanuel Lacic, Christoph Trattner:
TagRec: towards a standardized tag recommender benchmarking framework. HT 2014: 305-307
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Emanuel Lacic, Dominik Kowald, Paul Seitlinger, Christoph Trattner, Denis Parra:
Recommending Items in Social Tagging Systems Using Tag and Time Informations. HT (Doctoral Consortium / Late-breaking Results / Workshops) 2014
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Emanuel Lacic, Dominik Kowald, Christoph Trattner:
SocRecM: a scalable social recommender engine for online marketplaces. HT 2014: 308-310
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Dominik Kowald, Paul Seitlinger, Christoph Trattner, Tobias Ley:
Long time no see: the probability of reusing tags as a function of frequency and recency. WWW (Companion Volume) 2014: 463-468
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Emanuel Lacic, Dominik Kowald, Denis Parra, Martin Kahr, Christoph Trattner:
Towards a scalable social recommender engine for online marketplaces: the case of apache solr. WWW (Companion Volume) 2014: 817-822
2013
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Paul Seitlinger, Dominik Kowald, Christoph Trattner, Tobias Ley:
Recommending tags with a model of human categorization. CIKM 2013: 2381-2386
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Dominik Kowald, Sebastian Dennerlein, Dieter Theiler, Simon Walk, Christoph Trattner:
The Social Semantic Server - A Framework to Provide Services on Social Semantic Network Data. I-SEMANTICS (Posters & Demos) 2013: 50-54
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Dominik Kowald, Simone Kopeinik, Paul Seitlinger, Tobias Ley, Dietrich Albert, Christoph Trattner:
Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context. MSM/MUSE 2013: 55-74
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Dominik Kowald, Paul Seitlinger, Simone Kopeinik, Tobias Ley, Christoph Trattner:
Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender. MSM/MUSE 2013: 75-95
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Emanuel Lacic, Dominik Kowald, Lukas Eberhard, Christoph Trattner, Denis Parra, Leandro Balby Marinho:
Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces. MSM/MUSE 2013: 96-115

Data and Artifacts

see FAQ

What is the meaning of the colors in the publication lists?

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

Informal and Other Publications

see FAQ

What is the meaning of the colors in the publication lists?

2024
[i51]
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Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. CoRR abs/2401.03883 (2024)
[i50]
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  - journals/corr/abs-2406-11323
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Dominik Kowald:
Transparency, Privacy, and Fairness in Recommender Systems. CoRR abs/2406.11323 (2024)
[i49]
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Gustavo Escobedo, Marta Moscati, Peter Muellner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. CoRR abs/2406.11505 (2024)
[i48]
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  - journals/corr/abs-2406-14325
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Harald Semmelrock, Tony Ross-Hellauer, Simone Kopeinik, Dieter Theiler, Armin Haberl, Stefan Thalmann, Dominik Kowald:
Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers. CoRR abs/2406.14325 (2024)
[i47]
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  - journals/corr/abs-2407-09147
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Tomislav Duricic, Peter Müllner, Nicole Weidinger, Neven A. M. ElSayed, Dominik Kowald, Eduardo E. Veas:
AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments. CoRR abs/2407.09147 (2024)
2023
[i46]
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  - journals/corr/abs-2301-01037
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Emanuel Lacic, Tomislav Duricic, Leon Fadljevic, Dieter Theiler, Dominik Kowald:
Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings. CoRR abs/2301.01037 (2023)
[i45]
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  - journals/corr/abs-2302-03361
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Sebastian Scher, Bernhard Geiger, Simone Kopeinik, Andreas Trügler, Dominik Kowald:
A conceptual model for leaving the data-centric approach in machine learning. CoRR abs/2302.03361 (2023)
[i44]
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  - journals/corr/abs-2303-00400
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Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. CoRR abs/2303.00400 (2023)
[i43]
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  - journals/corr/abs-2307-10320
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Harald Semmelrock, Simone Kopeinik, Dieter Theiler, Tony Ross-Hellauer, Dominik Kowald:
Reproducibility in Machine Learning-Driven Research. CoRR abs/2307.10320 (2023)
[i42]
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  - journals/corr/abs-2310-02294
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Tomislav Duricic, Dominik Kowald, Emanuel Lacic, Elisabeth Lex:
Beyond-Accuracy: A Review on Diversity, Serendipity and Fairness in Recommender Systems Based on Graph Neural Networks. CoRR abs/2310.02294 (2023)
[i41]
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  - journals/corr/abs-2310-11967
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Armin Haberl, Jürgen Fleiß, Dominik Kowald, Stefan Thalmann:
Take the aTrain. Introducing an Interface for the Accessible Transcription of Interviews. CoRR abs/2310.11967 (2023)
2022
[i40]
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  - journals/corr/abs-2203-00376
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Dominik Kowald, Emanuel Lacic:
Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems. CoRR abs/2203.00376 (2022)
[i39]
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  - journals/corr/abs-2203-01256
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Emanuel Lacic, Dominik Kowald:
Recommendations in a Multi-Domain Setting: Adapting for Customization, Scalability and Real-Time Performance. CoRR abs/2203.01256 (2022)
[i38]
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  - journals/corr/abs-2206-11561
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Peter Müllner, Markus Schedl, Elisabeth Lex, Dominik Kowald:
ReuseKNN: Neighborhood Reuse for Privacy-Aware Recommendations. CoRR abs/2206.11561 (2022)
[i37]
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  - journals/corr/abs-2208-08881
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Sebastian Scher, Simone Kopeinik, Andreas Trügler, Dominik Kowald:
Long-term dynamics of fairness: understanding the impact of data-driven targeted help on job seekers. CoRR abs/2208.08881 (2022)
[i36]
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  - journals/corr/abs-2210-11828
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Peter Müllner, Stefan Schmerda, Dieter Theiler, Stefanie N. Lindstaedt, Dominik Kowald:
Towards Employing Recommender Systems for Supporting Data and Algorithm Sharing. CoRR abs/2210.11828 (2022)
2021
[i35]
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Peter Müllner, Dominik Kowald, Elisabeth Lex:
Robustness of Meta Matrix Factorization Against Strict Privacy Constraints. CoRR abs/2101.06927 (2021)
[i34]
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  - journals/corr/abs-2102-12188
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Dominik Kowald, Peter Müllner, Eva Zangerle, Christine Bauer, Markus Schedl, Elisabeth Lex:
Support the Underground: Characteristics of Beyond-Mainstream Music Listeners. CoRR abs/2102.12188 (2021)
[i33]
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  - journals/corr/abs-2108-06973
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Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? CoRR abs/2108.06973 (2021)
[i32]
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Peter Müllner, Elisabeth Lex, Dominik Kowald:
Position Paper on Simulating Privacy Dynamics in Recommender Systems. CoRR abs/2109.06473 (2021)
[i31]
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  - journals/corr/abs-2111-00562
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Tomislav Duricic, Dominik Kowald, Markus Schedl, Elisabeth Lex:
My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. CoRR abs/2111.00562 (2021)
[i30]
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  - journals/corr/abs-2111-14467
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Emanuel Lacic, Leon Fadljevic, Franz Weissenboeck, Stefanie N. Lindstädt, Dominik Kowald:
What Drives Readership? An Online Study on User Interface Types and Popularity Bias Mitigation in News Article Recommendations. CoRR abs/2111.14467 (2021)
2020
[i29]
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  - journals/corr/abs-2003-10699
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Dominik Kowald, Elisabeth Lex, Markus Schedl:
Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations. CoRR abs/2003.10699 (2020)
[i28]
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  - journals/corr/abs-2003-13345
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Tomislav Duricic, Hussain Hussain, Emanuel Lacic, Dominik Kowald, Denis Helic, Elisabeth Lex:
Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering. CoRR abs/2003.13345 (2020)
[i27]
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  - journals/corr/abs-2009-09935
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Markus Schedl, Christine Bauer, Wolfgang Reisinger, Dominik Kowald, Elisabeth Lex:
Listener Modeling and Context-aware Music Recommendation Based on Country Archetypes. CoRR abs/2009.09935 (2020)
2019
[i26]
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Dominik Kowald, Simone Kopeinik, Elisabeth Lex:
The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems. CoRR abs/1901.00306 (2019)
[i25]
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  - journals/corr/abs-1907-09781
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Dominik Kowald, Elisabeth Lex, Markus Schedl:
Modeling Artist Preferences of Users with Different Music Consumption Patterns for Fair Music Recommendations. CoRR abs/1907.09781 (2019)
[i24]
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  - journals/corr/abs-1907-11620
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Tomislav Duricic, Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
Exploiting weak ties in trust-based recommender systems using regular equivalence. CoRR abs/1907.11620 (2019)
[i23]
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  - journals/corr/abs-1908-00977
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Elisabeth Lex, Dominik Kowald:
The Impact of Time on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. CoRR abs/1908.00977 (2019)
[i22]
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  - journals/corr/abs-1908-04017
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Dominik Kowald, Matthias Traub, Dieter Theiler, Heimo Gursch, Emanuel Lacic, Stefanie N. Lindstaedt, Roman Kern, Elisabeth Lex:
Using the Open Meta Kaggle Dataset to Evaluate Tripartite Recommendations in Data Markets. CoRR abs/1908.04017 (2019)
[i21]
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  - journals/corr/abs-1908-04042
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Emanuel Lacic, Dominik Kowald, Dieter Theiler, Matthias Traub, Lucky Kuffer, Stefanie N. Lindstaedt, Elisabeth Lex:
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric. CoRR abs/1908.04042 (2019)
[i20]
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  - journals/corr/abs-1912-04696
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Dominik Kowald, Markus Schedl, Elisabeth Lex:
The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. CoRR abs/1912.04696 (2019)
2018
[i19]
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  - journals/corr/abs-1803-02179
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Dominik Kowald, Paul Seitlinger, Tobias Ley, Elisabeth Lex:
The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study. CoRR abs/1803.02179 (2018)
[i18]
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  - journals/corr/abs-1803-03176
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Dominik Kowald:
Modeling Activation Processes in Human Memory to Improve Tag Recommendations. CoRR abs/1803.03176 (2018)
[i17]
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  - journals/corr/abs-1805-03067
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Dominik Kowald, Elisabeth Lex:
Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms. CoRR abs/1805.03067 (2018)
[i16]
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  - journals/corr/abs-1805-11878
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Dominik Kowald:
Modeling Cognitive Processes in Social Tagging to Improve Tag Recommendations. CoRR abs/1805.11878 (2018)
[i15]
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  - journals/corr/abs-1807-06839
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Tomislav Duricic, Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
Trust-Based Collaborative Filtering: Tackling the Cold Start Problem Using Regular Equivalence. CoRR abs/1807.06839 (2018)
[i14]
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  - journals/corr/abs-1808-04603
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Dominik Kowald, Emanuel Lacic, Dieter Theiler, Elisabeth Lex:
AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments. CoRR abs/1808.04603 (2018)
[i13]
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Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations. CoRR abs/1808.06417 (2018)
[i12]
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Dominik Kowald, Elisabeth Lex:
Studying Confirmation Bias in Hashtag Usage on Twitter. CoRR abs/1809.03203 (2018)
[i11]
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Elisabeth Lex, Mario Wagner, Dominik Kowald:
Mitigating Confirmation Bias on Twitter by Recommending Opposing Views. CoRR abs/1809.03901 (2018)
2017
[i10]
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Dominik Kowald, Subhash Chandra Pujari, Elisabeth Lex:
Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. CoRR abs/1701.01276 (2017)
[i9]
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Emanuel Lacic, Dominik Kowald, Markus Reiter-Haas, Valentin Slawicek, Elisabeth Lex:
Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendations. CoRR abs/1711.07762 (2017)
2016
[i8]
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Dominik Kowald, Elisabeth Lex:
The Influence of Frequency, Recency and Semantic Context on the Reuse of Tags in Social Tagging Systems. CoRR abs/1604.00837 (2016)
[i7]
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Emanuel Lacic, Dominik Kowald, Elisabeth Lex:
High Enough? Explaining and Predicting Traveler Satisfaction Using Airline Review. CoRR abs/1604.00942 (2016)
2015
[i6]
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  - journals/corr/SeitlingerKKHLL15
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Paul Seitlinger, Dominik Kowald, Simone Kopeinik, Ilire Hasani-Mavriqi, Tobias Ley, Elisabeth Lex:
Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics. CoRR abs/1501.07716 (2015)
2014
[i5]
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  - journals/corr/KowaldSTL14
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Dominik Kowald, Paul Seitlinger, Christoph Trattner, Tobias Ley:
Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender. CoRR abs/1402.0728 (2014)
[i4]
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  - journals/corr/LacicKETPM14
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Emanuel Lacic, Dominik Kowald, Lukas Eberhard, Christoph Trattner, Denis Parra, Leandro Balby Marinho:
Utilizing Online Social Network and Location-Based Data to Recommend Items in an Online Marketplace. CoRR abs/1405.1837 (2014)
[i3]
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Emanuel Lacic, Dominik Kowald, Christoph Trattner:
SocRecM: A Scalable Social Recommender Engine for Online Marketplaces. CoRR abs/1405.1842 (2014)
[i2]
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Emanuel Lacic, Dominik Kowald, Paul Seitlinger, Christoph Trattner, Denis Parra:
Recommending Items in Social Tagging Systems Using Tag and Time Information. CoRR abs/1406.7727 (2014)
2013
[i1]
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  - journals/corr/KowaldSTL13
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Dominik Kowald, Paul Seitlinger, Christoph Trattner, Tobias Ley:
Long Time No See: The Probability of Reusing Tags as a Function of Frequency and Recency. CoRR abs/1312.5111 (2013)

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