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Dominik Kowald
Dominik Kowald
Research Area Manager, FAIR-AI, Know-Center, Graz University of Technology
Verified email at tugraz.at - Homepage
Title
Cited by
Cited by
Year
The unfairness of popularity bias in music recommendation: A reproducibility study
D Kowald, M Schedl, E Lex
Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020
1742020
Temporal effects on hashtag reuse in twitter: A cognitive-inspired hashtag recommendation approach
D Kowald, SC Pujari, E Lex
Proceedings of the 26th International Conference on World Wide Web, 1401-1410, 2017
862017
Psychology-informed recommender systems
E Lex, D Kowald, P Seitlinger, TNT Tran, A Felfernig, M Schedl
Foundations and trends® in information retrieval 15 (2), 134-242, 2021
772021
Analyzing item popularity bias of music recommender systems: are different genders equally affected?
O Lesota, A Melchiorre, N Rekabsaz, S Brandl, D Kowald, E Lex, ...
Proceedings of the 15th ACM conference on recommender systems, 601-606, 2021
702021
Recommending tags with a model of human categorization
P Seitlinger, D Kowald, C Trattner, T Ley
Proceedings of the 22nd ACM international conference on Information …, 2013
502013
High Enough? explaining and predicting traveler Satisfaction using airline reviews
E Lacic, D Kowald, E Lex
Proceedings of the 27th ACM Conference on Hypertext and Social Media, 249-254, 2016
492016
Support the underground: characteristics of beyond-mainstream music listeners
D Kowald, P Muellner, E Zangerle, C Bauer, M Schedl, E Lex
EPJ Data Science 10 (1), 14, 2021
472021
Trust-based collaborative filtering: Tackling the cold start problem using regular equivalence
T Duricic, E Lacic, D Kowald, E Lex
Proceedings of the 12th ACM conference on recommender systems, 446-450, 2018
422018
Listener modeling and context-aware music recommendation based on country archetypes
M Schedl, C Bauer, W Reisinger, D Kowald, E Lex
Frontiers in Artificial Intelligence 3, 508725, 2021
372021
Long time no see: The probability of reusing tags as a function of frequency and recency
D Kowald, P Seitlinger, C Trattner, T Ley
Proceedings of the 23rd international conference on world wide web, 463-468, 2014
332014
The tagrec framework as a toolkit for the development of tag-based recommender systems
D Kowald, S Kopeinik, E Lex
Adjunct publication of the 25th conference on user modeling, adaptation and …, 2017
322017
The influence of frequency, recency and semantic context on the reuse of tags in social tagging systems
D Kowald, E Lex
Proceedings of the 27th ACM Conference on Hypertext and Social Media, 237-242, 2016
322016
Which algorithms suit which learning environments? A comparative study of recommender systems in TEL
S Kopeinik, D Kowald, E Lex
Adaptive and Adaptable Learning: 11th European Conference on Technology …, 2016
322016
Modeling Popularity and Temporal Drift of Music Genre Preferences.
E Lex, D Kowald, M Schedl
Trans. Int. Soc. Music. Inf. Retr. 3 (1), 17-30, 2020
312020
Tagrec: Towards a standardized tag recommender benchmarking framework
D Kowald, E Lacic, C Trattner
Proceedings of the 25th ACM conference on Hypertext and social media, 305-307, 2014
312014
Using autoencoders for session-based job recommendations
E Lacic, M Reiter-Haas, D Kowald, M Reddy Dareddy, J Cho, E Lex
User Modeling and User-Adapted Interaction 30, 617-658, 2020
302020
Modeling Activation Processes in Human Memory to Predict the Use of Tags in Social Bookmarking Systems.
C Trattner, D Kowald, P Seitlinger, T Ley, S Kopeinik
J. Web Sci. 2 (1), 1-16, 2016
302016
Attention please! a hybrid resource recommender mimicking attention-interpretation dynamics
P Seitlinger, D Kowald, S Kopeinik, I Hasani-Mavriqi, E Lex, T Ley
Proceedings of the 24th International Conference on World Wide Web, 339-345, 2015
302015
Evaluating tag recommender algorithms in real-world folksonomies: A comparative study
D Kowald, E Lex
Proceedings of the 9th ACM Conference on Recommender Systems, 265-268, 2015
292015
Refining frequency-based tag reuse predictions by means of time and semantic context
D Kowald, S Kopeinik, P Seitlinger, T Ley, D Albert, C Trattner
Mining, Modeling, and Recommending Things in Social Media: 4th International …, 2015
292015
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