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Tessa Grosz

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Journal Articles

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2024
[j1]
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  dblp key:
  - journals/fdata/KumarGRGS24
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  - https://dblp.org/rec/journals/fdata/KumarGRGS24
Deepak Kumar, Tessa Grosz, Navid Rekabsaz, Elisabeth Greif, Markus Schedl:
Fairness of recommender systems in the recruitment domain: an analysis from technical and legal perspectives. Frontiers Big Data 6 (2024)

Conference and Workshop Papers

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2023
[c2]
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  dblp key:
  - conf/hr-recsys/KumarGGRS23
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Deepak Kumar, Tessa Grosz, Elisabeth Greif, Navid Rekabsaz, Markus Schedl:
Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning. HR@RecSys 2023
2022
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  - conf/um/SchedlRLGG22
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Markus Schedl, Navid Rekabsaz, Elisabeth Lex, Tessa Grosz, Elisabeth Greif:
Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research. UMAP (Adjunct Publication) 2022: 90-94

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