Abstract
The reproducibility crisis, spanning across various scientific fields, substantially affects information retrieval research [1].
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References
Baker, M.: 1,500 Scientists lift the lid on reproducibility. Nature 533,(7604) (2016)
Balog, K., Maxwell, D., Thomas, P., Zhang, S.: Report on the 1st simulation for information retrieval workshop (Sim4IR 2021) at SIGIR2021. In: ACM SIGIR Forum vol. 55, no. 2 (2022)
Balog, K., Zhai, C.: User Simulation for Evaluating Information Access Systems. arXiv preprint arXiv:2306.08550 (2023)
Breuer, T., Fuhr, N., Schaer, P.: Validating simulations of user query variants. In: Hagen, M., Verberne, S., Macdonald, C., Seifert, C., Balog, K., Nørvåg, K., Setty, V. (eds.) ECIR 2022. LNCS, vol. 13185, pp. 80–94. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-99736-6_6
Breuer, T.: Reproducible Information Retrieval Research: From Principled System-Oriented Evaluations Towards User-Oriented Experimentation, University of Duisburg-Essen (2023)
Ferro, N., Fuhr, N., Jarvelin, K., Kando, N., Lippold, M., Zobel, J.: Increasing reproducibility in IR: findings from the dagstuhl seminar on” reproducibility of data-oriented experiments in e-science. In: ACM SIGIR Forum. vol. 50, no. 1, pp. 68–82. ACM, New York, NY, USA (2016)
Fuhr, N.: A probability ranking principle for interactive information retrieval. Inf. Retrieval 11(3), 251–265 (2008)
Kelly, D.: Methods for evaluating interactive information retrieval systems with users. Found. Trends in Inf. Retrieval 3(1–2), 1–224 (2009)
Liu, J., Shah, C.: Interactive IR user study design, evaluation, and reporting. Morgan & Claypool Publishers (2019)
Maistro, M., Breuer, T., Schaer, P., Ferro, N.: An in-depth investigation on the behavior of measures to quantify reproducibility. Inf. Process. & Manage 60(3), 103332 (2023)
Maxwell, D., Azzopardi, L.: Simulating interactive information retrieval: SimIIR: A framework for the simulation of interaction. In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, SIGIR 2016, pp. 1141–1144. ACM, Pisa, Italy (2016)
Petras, V., Bogers, T., Gade, M.: Elements of IIR studies: a review of the 2006-2018 IIiX and CHIIR conferences. In: CEUR Workshop Proceedings, vol. 2337, pp. 37–41 (2019)
Tran, V.: Modellierung von Benutzerverhalten im interaktiven Retrieval mit Markov-Ketten, University of Duisburg-Essen (2020)
Yang, G.H., Dong, X., Luo, J., Zhang, S.: Session search modeling by partially observable Markov decision process. Inform. Retrieval J. 21(1), 56–80 (2017). https://doi.org/10.1007/s10791-017-9316-8
Zerhoudi, S., et al.: The SimIIR 2.0 framework: user types, markov model-based interaction simulation, and advanced query generation. In: Proceedings of the 31st ACM International Conference on Information and Knowledge Management, pp. 4661–4666 (2022)
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Friese, J.I. (2024). Reproduction and Simulation of Interactive Retrieval Experiments. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham. https://doi.org/10.1007/978-3-031-56069-9_40
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