| Investigating gender fairness of recommendation algorithms in the music domain AB Melchiorre, N Rekabsaz, E Parada-Cabaleiro, S Brandl, O Lesota, ... Information Processing & Management 58 (5), 102666, 2021 | 120 | 2021 |
| Volatility prediction using financial disclosures sentiments with word embedding-based IR models N Rekabsaz, M Lupu, A Baklanov, A Hanbury, A Dür, L Anderson Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 89 | 2017 |
| Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers N Rekabsaz, S Kopeinik, M Schedl Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 66 | 2021 |
| Do Neural Ranking Models Intensify Gender Bias? N Rekabsaz, M Schedl Proceedings of the 43rd International ACM SIGIR conference on research and …, 2020 | 66 | 2020 |
| 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 | 57 | 2021 |
| Exploration of a threshold for similarity based on uncertainty in word embedding N Rekabsaz, M Lupu, A Hanbury Advances in Information Retrieval: 39th European Conference on IR Research …, 2017 | 53 | 2017 |
| WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models B Minixhofer, F Paischer, N Rekabsaz Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 47 | 2022 |
| On the effect of low-frequency terms on neural-IR models S Hofstätter, N Rekabsaz, C Eickhoff, A Hanbury Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 40 | 2019 |
| LFM-2b: A dataset of enriched music listening events for recommender systems research and fairness analysis M Schedl, S Brandl, O Lesota, E Parada-Cabaleiro, D Penz, N Rekabsaz Proceedings of the 2022 Conference on Human Information Interaction and …, 2022 | 39 | 2022 |
| Tripclick: the log files of a large health web search engine N Rekabsaz, O Lesota, M Schedl, J Brassey, C Eickhoff Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 38 | 2021 |
| Word embedding causes topic shifting; exploit global context! N Rekabsaz, M Lupu, A Hanbury, H Zamani Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 34 | 2017 |
| Generalizing translation models in the probabilistic relevance framework N Rekabsaz, M Lupu, A Hanbury, G Zuccon Proceedings of the 25th ACM international on conference on information and …, 2016 | 33 | 2016 |
| Mitigating bias in search results through contextual document reranking and neutrality regularization G Zerveas, N Rekabsaz, D Cohen, C Eickhoff Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 32 | 2022 |
| Unlearning protected user attributes in recommendations with adversarial training C Ganhör, D Penz, N Rekabsaz, O Lesota, M Schedl Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 31* | 2022 |
| Grep-biasir: A dataset for investigating gender representation bias in information retrieval results K Krieg, E Parada-Cabaleiro, G Medicus, O Lesota, M Schedl, ... Proceedings of the 2023 Conference on Human Information Interaction and …, 2023 | 30 | 2023 |
| Not all relevance scores are equal: Efficient uncertainty and calibration modeling for deep retrieval models D Cohen, B Mitra, O Lesota, N Rekabsaz, C Eickhoff Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 29 | 2021 |
| Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence N Rekabsaz, R West, J Henderson, A Hanbury Proceedings of the International AAAI Conference on Web and Social Media, 2021 | 20 | 2021 |
| Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? K Krieg, E Parada-Cabaleiro, M Schedl, N Rekabsaz International Workshop on Algorithmic Bias in Search and Recommendation, 104-116, 2022 | 18 | 2022 |
| A modern perspective on query likelihood with deep generative retrieval models O Lesota, N Rekabsaz, D Cohen, KA Grasserbauer, C Eickhoff, M Schedl Proceedings of the 2021 ACM SIGIR International Conference on Theory of …, 2021 | 18 | 2021 |
| Enriching word embeddings for patent retrieval with global context S Hofstätter, N Rekabsaz, M Lupu, C Eickhoff, A Hanbury Advances in Information Retrieval: 41st European Conference on IR Research …, 2019 | 18 | 2019 |
Markus SchedlProfessor at Johannes Kepler University Linz, Institute of Computational Perception在 jku.at 的电子邮件经过验证
