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Simulating user interactions enables a more user-oriented evaluation of information retrieval (IR) systems.
Krebs, J.R., Ryan, J.C., Charnov, E.L.: Hunting by expectation or optimal foraging? a study of patch use by chickadees. Animal Behaviour 22
1974
Earlier work this paper cites.
Tague, J., Nelson, M.J., Wu, H.: Problems in the simulation of bibliographic retrieval systems. In: Oddy, R.N., Robertson, S.E., van Rijsbergen, C.J., Williams, P.W. (eds.) Information Retrieval Research, Proc. Joint ACM/BCS Symposium in Information Storage and Retrieval, Cambridge, UK, June 1980. pp. 236–255. Butterworths (1980), http://dl.acm.org/citation.cfm?id=636684
1980
Earlier work this paper cites.
Tague, J., Nelson, M.J.: Simulation of user judgments in bibliographic retrieval systems. In: Crouch, C.J. (ed.) Theoretical Issues in Information Retrieval, Proceedings of the Fourth International Conference on Information Storage and Retrieval, Oakland, California, USA, May 31 - June 2, 1981. pp. 66–71. ACM (1981). https://doi.org/10.1145/511754.511764, https://doi.org/10.1145/511754.511764
1981
Earlier work this paper cites.
Hersh, W.R., Turpin, A., Price, S., Chan, B., Kraemer, D., Sacherek, L., Olson, D.: Do batch and user evaluation give the same results? In: Yannakoudakis, E.J., Belkin, N.J., Ingwersen, P., Leong, M.K. (eds.) SIGIR 2000: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 24-28, 2000, Athens, Greece. pp. 17–24. ACM (2000). https://doi.org/10.1145/345508.345539, https://doi.org/10.1145/345508.345539
2000
Earlier work this paper cites.
Järvelin, K., Kekäläinen, J.: IR evaluation methods for retrieving highly relevant documents. In: SIGIR. pp. 41–48. ACM (2000)
2000
Earlier work this paper cites.
Turpin, A., Hersh, W.R.: Why batch and user evaluations do not give the same results. In: Croft, W.B., Harper, D.J., Kraft, D.H., Zobel, J. (eds.) SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, September 9-13, 2001, New Orleans, Louisiana, USA. pp. 225–231. ACM (2001). https://doi.org/10.1145/383952.383992, https://doi.org/10.1145/383952.383992
2001
Earlier work this paper cites.
Järvelin, K., Price, S.L., Delcambre, L.M.L., Nielsen, M.L.: Discounted cumulated gain based evaluation of multiple-query IR sessions. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds.) Advances in Information Retrieval , 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008. Proceedings. Lecture Notes in Computer Science, vol. 4956, pp. 4–15. Springer (2008). https://doi.org/10.1007/978-3-540-78646-7_4, https://doi.org/10.1007/978-3-540-78646-7_4
2008
Earlier work this paper cites.
Moffat, A., Zobel, J.: Rank-biased precision for measurement of retrieval effectiveness. ACM Trans. Inf. Syst. 27
2008
Earlier work this paper cites.
Robertson, S.E., Zaragoza, H.: The probabilistic relevance framework: BM25 and beyond. Found. Trends Inf. Retr. 3
2009
Earlier work this paper cites.
Azzopardi, L., Järvelin, K., Kamps, J., Smucker, M.D.: Report on the SIGIR 2010 workshop on the simulation of interaction. SIGIR Forum 44
2010
Earlier work this paper cites.
Baskaya, F., Keskustalo, H., Järvelin, K.: Modeling behavioral factors in interactive information retrieval. In: He, Q., Iyengar, A., Nejdl, W., Pei, J., Rastogi, R. (eds.) 22nd ACM International Conference on Information and Knowledge Management, CIKM’13, San Francisco, CA, USA, October 27 - November 1, 2013. pp. 2297–2302. ACM (2013). https://doi.org/10.1145/2505515.2505660, https://doi.org/10.1145/2505515.2505660
2013
Earlier work this paper cites.
Hofmann, K., Schuth, A., Whiteson, S., de Rijke, M.: Reusing historical interaction data for faster online learning to rank for IR. In: Leonardi, S., Panconesi, A., Ferragina, P., Gionis, A. (eds.) Sixth ACM International Conference on Web Search and Data Mining, WSDM 2013, Rome, Italy, February 4-8, 2013. pp. 183–192. ACM (2013). https://doi.org/10.1145/2433396.2433419, https://doi.org/10.1145/2433396.2433419
2013
Earlier work this paper cites.
Carterette, B., Bah, A., Zengin, M.: Dynamic test collections for retrieval evaluation. In: Allan, J., Croft, W.B., de Vries, A.P., Zhai, C. (eds.) Proceedings of the 2015 International Conference on the Theory of Information Retrieval, ICTIR 2015, Northampton, Massachusetts, USA, September 27-30, 2015. pp. 91–100. ACM (2015). https://doi.org/10.1145/2808194.2809470, https://doi.org/10.1145/2808194.2809470
2015
Earlier work this paper cites.
Maxwell, D., Azzopardi, L., Järvelin, K., Keskustalo, H.: Searching and stopping: An analysis of stopping rules and strategies. In: CIKM. pp. 313–322. ACM (2015)
2015
Cited alongside, same era.
Hagen, M., Michel, M., Stein, B.: Simulating ideal and average users. In: AIRS. Lecture Notes in Computer Science, vol. 9994, pp. 138–154. Springer (2016)
2016
Cited alongside, same era.
Maxwell, D., Azzopardi, L.: Simulating interactive information retrieval: SimIIR: A framework for the simulation of interaction. In: SIGIR. pp. 1141–1144. ACM (2016)
2016
Cited alongside, same era.
Allan, J., Harman, D., Kanoulas, E., Li, D., Gysel, C.V., Voorhees, E.M.: TREC 2017 common core track overview. In: TREC. NIST Special Publication, vol. 500–324. National Institute of Standards and Technology (NIST) (2017)
2017
Cited alongside, same era.
Günther, S., Hagen, M.: Assessing query suggestions for search session simulation. Sim4IR: The SIGIR 2021 Workshop on Simulation for Information Retrieval Evaluation (2021), http://ceur-ws.org/Vol-2911/paper6.pdf
2021
Later among the works it cites.
MacAvaney, S., Yates, A., Feldman, S., Downey, D., Cohan, A., Goharian, N.: Simplified data wrangling with ir_datasets. In: Diaz, F., Shah, C., Suel, T., Castells, P., Jones, R., Sakai, T. (eds.) SIGIR ’21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021. pp. 2429–2436. ACM (2021). https://doi.org/10.1145/3404835.3463254, https://doi.org/10.1145/3404835.3463254
2021
Later among the works it cites.
Macdonald, C., Tonellotto, N., MacAvaney, S., Ounis, I.: PyTerrier: Declarative experimentation in python from BM25 to dense retrieval. In: CIKM. pp. 4526–4533. ACM (2021)
2021
Later among the works it cites.
Breuer, T., Fuhr, N., Schaer, P.: Validating simulations of user query variants. In: ECIR (1). Lecture Notes in Computer Science, vol. 13185, pp. 80–94. Springer (2022)
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Pääkkönen, T., Kekäläinen, J., Keskustalo, H., Azzopardi, L., Maxwell, D., Järvelin, K.: Validating simulated interaction for retrieval evaluation. Inf. Retr. J. 20
2017
Cited alongside, same era.
Zhang, Y., Liu, X., Zhai, C.: Information retrieval evaluation as search simulation: A general formal framework for IR evaluation. In: ICTIR. pp. 193–200. ACM (2017)
2017
Cited alongside, same era.
Voorhees, E.M., Ellis, A. (eds.): Proceedings of the Twenty-Seventh Text REtrieval Conference, TREC 2018, Gaithersburg, Maryland, USA, November 14-16, 2018, NIST Special Publication, vol. 500–331. National Institute of Standards and Technology (NIST) (2018), https://trec.nist.gov/pubs/trec27/trec2018.html
2018
Cited alongside, same era.
Lipani, A., Carterette, B., Yilmaz, E.: From a user model for query sessions to session rank biased precision (sRBP). In: Fang, Y., Zhang, Y., Allan, J., Balog, K., Carterette, B., Guo, J. (eds.) Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2019, Santa Clara, CA, USA, October 2-5, 2019. pp. 109–116. ACM (2019). https://doi.org/10.1145/3341981.3344216, https://doi.org/10.1145/3341981.3344216
2019
Cited alongside, same era.
Maxwell, D.: Modelling search and stopping in interactive information retrieval. Ph.D. thesis, University of Glasgow, UK (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Nogueira, R.F., Jiang, Z., Pradeep, R., Lin, J.: Document ranking with a pretrained sequence-to-sequence model. In: EMNLP (Findings). Findings of ACL, vol. EMNLP 2020, pp. 708–718. Association for Computational Linguistics (2020)
2020
Cited alongside, same era.
Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., von Platen, P., Ma, C., Jernite, Y., Plu, J., Xu, C., Scao, T.L., Gugger, S., Drame, M., Lhoest, Q., Rush, A.M.: Transformers: State-of-the-art natural language processing. In: Liu, Q., Schlangen, D. (eds.) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, EMNLP 2020 - Demos, Online, November 16-20, 2020. pp. 38–45. Association for Computational Linguistics (2020). https://doi.org/10.18653/V1/2020.EMNLP-DEMOS.6, https://doi.org/10.18653/v1/2020.emnlp-demos.6
2020
Cited alongside, same era.
2022
Later among the works it cites.
Scells, H., Zhuang, S., Zuccon, G.: Reduce, reuse, recycle: Green information retrieval research. In: SIGIR. pp. 2825–2837. ACM (2022)
2022
Later among the works it cites.
Zerhoudi, S., Günther, S., Plassmeier, K., Borst, T., Seifert, C., Hagen, M., Granitzer, M.: The SimIIR 2.0 framework: User types, markov model-based interaction simulation, and advanced query generation. In: CIKM. pp. 4661–4666. ACM (2022)
2022
Later among the works it cites.
Alaofi, M., Gallagher, L., Sanderson, M., Scholer, F., Thomas, P.: Can generative llms create query variants for test collections? an exploratory study. In: SIGIR. pp. 1869–1873. ACM (2023)
2023
Closest in time.
Balog, K., Zhai, C.: User simulation for evaluating information access systems. CoRR abs/2306.08550
2023
Closest in time.
Breuer, T., Fuhr, N., Schaer, P.: Validating synthetic usage data in living lab environments. J. Data and Information Quality (sep 2023). https://doi.org/10.1145/3623640, https://doi.org/10.1145/3623640 , just Accepted
2023
Closest in time.
Engelmann, B., Breuer, T., Schaer, P.: Simulating users in interactive web table retrieval. In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. p. 3875–3879. CIKM ’23, Association for Computing Machinery, New York, NY, USA (2023). https://doi.org/10.1145/3583780.3615187, https://doi.org/10.1145/3583780.3615187
2023
Closest in time.
Mackie, I., Chatterjee, S., Dalton, J.: Generative relevance feedback with large language models. In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. p. 2026–2031. SIGIR ’23, ACM (Jul 2023). https://doi.org/10.1145/3539618.3591992, http://dx.doi.org/10.1145/3539618.3591992
2023
Closest in time.
Wang, L., Yang, N., Wei, F.: Query2doc: Query expansion with large language models. In: Conference on Empirical Methods in Natural Language Processing. p. 9414–9423. Association for Computational Linguistics (2023)
2023
Closest in time.
Wang, X., MacAvaney, S., Macdonald, C., Ounis, I.: Generative query reformulation for effective adhoc search (2023)
2023
Closest in time.