| Mitigating popularity bias in recommendation: Potential and limits of calibration approaches A Klimashevskaia, M Elahi, D Jannach, C Trattner, L Skjærven International Workshop on Algorithmic Bias in Search and Recommendation, 82-90, 2022 | 13 | 2022 |
| Automatic news article generation from legislative proceedings: A phenom-based approach A Klimashevskaia, R Gadgil, T Gerrity, F Khosmood, C Gütl, P Howe International Conference on Statistical Language and Speech Processing, 15-26, 2021 | 5 | 2021 |
| Comparing the environmental impacts of recipes from four different recipe databases using Natural Language Processing C Reynolds, B Takacs, A Klimashevskaia, A Angelsen, R Ibáñez Martín, ... | 2 | 2021 |
| Addressing Popularity Bias in Recommender Systems: An Exploration of Self-Supervised Learning Models A Klimashevskaia, M Elahi, C Trattner Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation …, 2023 | 1 | 2023 |
| Popularity bias as ethical and technical issue in recommendation: A survey A Klimashevskaia Norsk IKT-konferanse for forskning og utdanning, 2022 | 1 | 2022 |
| Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study A Klimashevskaia, M Elahi, D Jannach, L Skjærven, A Tessem, C Trattner Proceedings of the 17th ACM Conference on Recommender Systems, 1084-1089, 2023 | | 2023 |
| A Survey on Popularity Bias in Recommender Systems A Klimashevskaia, D Jannach, M Elahi, C Trattner arXiv preprint arXiv:2308.01118, 2023 | | 2023 |
| To be or not to be central"-On the Stability of Network Centrality Measures in Shakespeare's" Hamlet A Klimashevskaia, BC Geiger, M Hagmüller, D Helic, F Fischer 15th Annual International Conference of the Alliance of Digital Humanities …, 2020 | | 2020 |
| Similarity Map Add-in for LibreOffice Calc K Gostiša, A Klimashevskaia, J Konda, G Moser | | 2019 |
Patrick HoweCalifornia Polytechnic State University, San Luis ObispoVerified email at calpoly.edu
