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Results: 21
Number of items: 21
  • Clarke, C. L. A., Kantor, P., Roegiest, A., Trippas, J. R., Ren, Z., Bucarelli, M. S., Fu, X., Fan, Y., Granitzer, M., Graus, D., Heuss, M., Kamps, J., Lei, Y., Parry, A., Reijnaers, D., de Rijke, M., Singh, S. A. K., Tang, Y., Verberne, S., ... Zhao, J. (2025). Report on the 2nd Search Futures Workshop at ECIR 2025. SIGIR Forum, 59(1). https://doi.org/10.1145/3769733.3769742
  • Open Access
    Fabris, A., Baranowska, N., Dennis, M. J., Graus, D., Hacker, P., Saldivar, J., Zuiderveen Borgesius, F., & Biega, A. J. (2025). Fairness and Bias in Algorithmic Hiring: A Multidisciplinary Survey. ACM Transactions on Intelligent Systems and Technology, 16(1), Article 16. https://doi.org/10.1145/3696457
  • Open Access
    Vrolijk, J., & Graus, D. (2023). Enhancing PLM Performance on Labour Market Tasks via Instruction-based Finetuning and Prompt-tuning with Rules. In M. Kaya, T. Bogers, D. Graus, C. Johnson, & J.-J. Decorte (Eds.), Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR 2023): co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023) : Singapore, Singapore, 18th-22nd September 2023 Article 4 (CEUR Workshop Proceedings; Vol. 3490). CEUR-WS. https://ceur-ws.org/Vol-3490/RecSysHR2023-paper_4.pdf
  • Open Access
    Arafan, A. M., Graus, D., Santos, F. P., & Beauxis-Aussalet, E. (2022). End-to-End Bias Mitigation in Candidate Recommender Systems with Fairness Gates. In M. Kaya, T. Bogers, D. Graus, S. Mesbah, C. Johnson, & F. Gutiérrez (Eds.), Proceedings of the 2nd Workshop on Recommender Systems for Human Resources (RecSys-in-HR 2022): co-located with the 16th ACM Conference on Recommender Systems (RecSys 2022) : Seattle, USA, 18th-23rd September 2022 Article 6 (CEUR Workshop Proceedings; Vol. 3218). CEUR-WS. https://ceur-ws.org/Vol-3218/RecSysHR2022-paper_6.pdf
  • Sullivan, E., Bountouridis, D., Harambam, J., Najafian, S., Loecherbach, F., Makhortykh, M., Kelen, D., Wilkinson, D., Graus, D., & Tintarev, N. (2019). Reading news with a purpose: Explaining user profiles for self-actualization. In ACM UMAP '19 adjunct: adjunct publication of the 27th Conference on User Modeling, Adaptation and Personalization : June 9-12, 2019, Larnaca, Cyprus (pp. 241-245). The Association for Computing Machinery. https://doi.org/10.1145/3314183.3323456
  • Open Access
    Graus, D., Odijk, D., & de Rijke, M. (2018). The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams. Journal of the Association for Information Science and Technology, 69(6), 773-786. https://doi.org/10.1002/asi.24004
  • Open Access
    Graus, D. P. (2017). Entities of interest: Discovery in digital traces. [Thesis, fully internal, Universiteit van Amsterdam].
  • Graus, D., Bennett, P. N., White, R. W., & Horvitz, E. (2016). Analyzing and predicting task reminders. In UMAP'16: proceedings of the 2016 Conference on User Modeling Adaptation and Personalization : July 13-17, 2016, Halifax, Nova Scotia, Canada (pp. 7-15). The Association for Computing Machinery. https://doi.org/10.1145/2930238.2930239
  • Open Access
    de Rijke, M., & Graus, D. (2016). Wij zijn racisten, en daarom Google ook. NRC Handelsblad, 16.
  • Open Access
    Graus, D., Tsagkias, M., Weerkamp, W., Meij, E., & de Rijke, M. (2016). Dynamic collective entity representations for entity ranking. In WSDM'16 : proceedings of the Ninth ACM International Conference on Web Search and Data Mining : February 22-25, 2016, San Francisco, CA, USA (pp. 595-604). Association for Computing Machinery. https://doi.org/10.1145/2835776.2835819
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