{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T15:35:54Z","timestamp":1771515354841,"version":"3.50.1"},"publisher-location":"Cham","reference-count":61,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031887161","type":"print"},{"value":"9783031887178","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-88717-8_9","type":"book-chapter","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T12:10:06Z","timestamp":1743768606000},"page":"112-129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Combining Query Performance Predictors: A Reproducibility Study"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8091-0685","authenticated-orcid":false,"given":"Sourav","family":"Saha","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9220-6652","authenticated-orcid":false,"given":"Suchana","family":"Datta","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5962-5983","authenticated-orcid":false,"given":"Dwaipayan","family":"Roy","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9045-9971","authenticated-orcid":false,"given":"Mandar","family":"Mitra","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8065-5418","authenticated-orcid":false,"given":"Derek","family":"Greene","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,3]]},"reference":[{"key":"9_CR1","doi-asserted-by":"crossref","unstructured":"Ahmad, W.U., Chang, K., Wang, H.: Context attentive document ranking and query suggestion. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, pp. 385\u2013394. Association for Computing Machinery, New York (2019)","DOI":"10.1145\/3331184.3331246"},{"key":"9_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/978-3-540-24752-4_10","volume-title":"Advances in Information Retrieval","author":"G Amati","year":"2004","unstructured":"Amati, G., Carpineto, C., Romano, G.: Query difficulty, robustness, and selective application of query expansion. In: McDonald, S., Tait, J. (eds.) ECIR 2004. LNCS, vol. 2997, pp. 127\u2013137. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-24752-4_10"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Arabzadeh, N., Khodabakhsh, M., Bagheri, E.: BERT-QPP: contextualized pre-trained transformers for query performance prediction. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, CIKM 2021, pp. 2857\u20132861. Association for Computing Machinery, New York (2021)","DOI":"10.1145\/3459637.3482063"},{"key":"9_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1007\/978-3-540-71496-5_20","volume-title":"Advances in Information Retrieval","author":"JA Aslam","year":"2007","unstructured":"Aslam, J.A., Pavlu, V.: Query hardness estimation using Jensen-Shannon divergence among multiple scoring functions. In: Amati, G., Carpineto, C., Romano, G. (eds.) ECIR 2007. LNCS, vol. 4425, pp. 198\u2013209. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-71496-5_20"},{"key":"9_CR5","doi-asserted-by":"publisher","unstructured":"Bach, F.R.: Bolasso: model consistent lasso estimation through the bootstrap. In: Proceedings of the 25th International Conference on Machine Learning, ICML 2008, pp. 33\u201340. Association for Computing Machinery, New York (2008). https:\/\/doi.org\/10.1145\/1390156.1390161","DOI":"10.1145\/1390156.1390161"},{"key":"9_CR6","unstructured":"Banerjee, S., Pedersen, T.: Extended gloss overlaps as a measure of semantic relatedness. In: Proceedings of the 18th International Joint Conference on Artificial Intelligence, IJCAI 2003, pp. 805\u2013810. Morgan Kaufmann Publishers Inc., San Francisco (2003)"},{"key":"9_CR7","doi-asserted-by":"crossref","unstructured":"Breuer, T., et al.: How to measure the reproducibility of system-oriented IR experiments. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 349\u2013358 (2020)","DOI":"10.1145\/3397271.3401036"},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Butman, O., Shtok, A., Kurland, O., Carmel, D.: Query-performance prediction using minimal relevance feedback. In: Proceedings of the 2013 Conference on the Theory of Information Retrieval, ICTIR 2013, pp. 14\u201321. Association for Computing Machinery, New York (2013)","DOI":"10.1145\/2499178.2499201"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Carmel, D., Yom-Tov, E.: Estimating the query difficulty for information retrieval. In: Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010, pp.\u00a0911. Association for Computing Machinery, New York (2010)","DOI":"10.1145\/1835449.1835683"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Carmel, D., Yom-Tov, E., Darlow, A., Pelleg, D.: What makes a query difficult? In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2006, pp. 390\u2013397. Association for Computing Machinery, New York (2006)","DOI":"10.1145\/1148170.1148238"},{"key":"9_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1007\/978-3-030-99739-7_8","volume-title":"Advances in Information Retrieval","author":"X Chen","year":"2022","unstructured":"Chen, X., He, B., Sun, L.: Groupwise query performance prediction with BERT. In: Hagen, M., et al. (eds.) ECIR 2022. LNCS, vol. 13186, pp. 64\u201374. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-99739-7_8"},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Clarke, C., Craswell, N., Soboroff, I., Cormack, G.: Overview of the TREC 2010 web track. In: Proceedings of TREC (2010)","DOI":"10.6028\/NIST.SP.500-294.web-overview"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Clarke, C.L., Craswell, N., Soboroff, I.: Overview of the TREC 2004 terabyte track. In: Proceedings of the Thirteenth Text REtrieval Conference, TREC 2004, Gaithersburg, Maryland, USA, 13\u201316 November 2000 (2004)","DOI":"10.6028\/NIST.SP.500-261.terabyte-overview"},{"issue":"5","key":"9_CR14","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/s10791-011-9162-z","volume":"14","author":"GV Cormack","year":"2011","unstructured":"Cormack, G.V., Smucker, M.D., Clarke, C.: Efficient and effective spam filtering and re-ranking for large web datasets. Inf. Retr. 14(5), 441\u2013465 (2011)","journal-title":"Inf. Retr."},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Cronen-Townsend, S., Zhou, Y., Croft, W.B.: Predicting query performance. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2002, pp. 299\u2013306. Association for Computing Machinery, New York (2002)","DOI":"10.1145\/564376.564429"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Cronen-Townsend, S., Zhou, Y., Croft, W.B.: A framework for selective query expansion. In: Proceedings of the Thirteenth ACM International Conference on Information and Knowledge Management, CIKM 2004, pp. 236\u2013237. Association for Computing Machinery, New York (2004)","DOI":"10.1145\/1031171.1031220"},{"issue":"6","key":"9_CR17","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s10791-006-9006-4","volume":"9","author":"S Cronen-Townsend","year":"2006","unstructured":"Cronen-Townsend, S., Zhou, Y., Croft, W.B.: Precision prediction based on ranked list coherence. Inf. Retrieval 9(6), 723\u2013755 (2006)","journal-title":"Inf. Retrieval"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Cummins, R., Jose, J., O\u2019Riordan, C.: Improved query performance prediction using standard deviation. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011, pp. 1089\u20131090 (2011)","DOI":"10.1145\/2009916.2010063"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Datta, S., Ganguly, D., Greene, D., Mitra, M.: Deep-QPP: a pairwise interaction-based deep learning model for supervised query performance prediction. In: WSDM 2022: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event, Tempe, AZ, USA, 21\u201325 February 2022, pp. 201\u2013209. ACM (2022)","DOI":"10.1145\/3488560.3498491"},{"key":"9_CR20","doi-asserted-by":"crossref","unstructured":"Datta, S., Ganguly, D., Mitra, M., Greene, D.: A relative information gain-based query performance prediction framework with generated query variants. ACM Trans. Inf. Syst. 41(2), 38:1\u201338:31 (2023)","DOI":"10.1145\/3545112"},{"key":"9_CR21","doi-asserted-by":"crossref","unstructured":"Datta, S., MacAvaney, S., Ganguly, D., Greene, D.: A \u2018pointwise-query, listwise-document\u2019 based query performance prediction approach. In: SIGIR 2022: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11\u201315 July 2022, pp. 2148\u20132153. ACM (2022)","DOI":"10.1145\/3477495.3531821"},{"key":"9_CR22","doi-asserted-by":"crossref","unstructured":"Diaz, F.: Performance prediction using spatial autocorrelation. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 583\u2013590. ACM, Amsterdam (2007)","DOI":"10.1145\/1277741.1277841"},{"issue":"2","key":"9_CR23","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1214\/009053604000000067","volume":"32","author":"B Efron","year":"2004","unstructured":"Efron, B., Hastie, T., Johnstone, I., Tibshirani, R.: Least angle regression. Ann. Stat. 32(2), 407\u2013451 (2004)","journal-title":"Ann. Stat."},{"key":"9_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/978-3-030-72113-8_8","volume-title":"Advances in Information Retrieval","author":"G Faggioli","year":"2021","unstructured":"Faggioli, G., Zendel, O., Culpepper, J.S., Ferro, N., Scholer, F.: An enhanced evaluation framework for query performance prediction. In: Hiemstra, D., Moens, M.-F., Mothe, J., Perego, R., Potthast, M., Sebastiani, F. (eds.) ECIR 2021. LNCS, vol. 12656, pp. 115\u2013129. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-72113-8_8"},{"key":"9_CR25","doi-asserted-by":"crossref","unstructured":"Feild, H., Allan, J.: Task-aware query recommendation. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2013, pp. 83\u201392. Association for Computing Machinery, New York (2013)","DOI":"10.1145\/2484028.2484069"},{"issue":"1","key":"9_CR26","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1145\/1842890.1842906","volume":"44","author":"C Hauff","year":"2010","unstructured":"Hauff, C.: Predicting the effectiveness of queries and retrieval systems. SIGIR Forum 44(1), 88 (2010)","journal-title":"SIGIR Forum"},{"key":"9_CR27","doi-asserted-by":"publisher","unstructured":"Hauff, C.: Predicting the effectiveness of queries and retrieval systems. Ph.D. thesis, University of Twente, Enschede, Netherlands (2010). https:\/\/doi.org\/10.3990\/1.9789036529532. http:\/\/eprints.eemcs.utwente.nl\/17338\/","DOI":"10.3990\/1.9789036529532"},{"key":"9_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1007\/978-3-642-00958-7_28","volume-title":"Advances in Information Retrieval","author":"C Hauff","year":"2009","unstructured":"Hauff, C., Azzopardi, L., Hiemstra, D.: The combination and evaluation of query performance prediction methods. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds.) ECIR 2009. LNCS, vol. 5478, pp. 301\u2013312. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-00958-7_28"},{"key":"9_CR29","doi-asserted-by":"crossref","unstructured":"Hauff, C., Hiemstra, D., de\u00a0Jong, F.: A survey of pre-retrieval query performance predictors. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM 2008, pp. 1419\u20131420. Association for Computing Machinery (2008)","DOI":"10.1145\/1458082.1458311"},{"key":"9_CR30","doi-asserted-by":"crossref","unstructured":"Hawking, D.: Overview of the TREC-9 web track. In: Proceedings of The Ninth Text REtrieval Conference, TREC 2000, Gaithersburg, Maryland, USA, 13\u201316 November 2000 (2000)","DOI":"10.6028\/NIST.SP.500-249.web-overview"},{"key":"9_CR31","doi-asserted-by":"crossref","unstructured":"He, B., Ounis, I.: Inferring query performance using pre-retrieval predictors. In: String Processing and Information Retrieval, pp. 43\u201354 (2004)","DOI":"10.1007\/978-3-540-30213-1_5"},{"key":"9_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1007\/978-3-540-78646-7_80","volume-title":"Advances in Information Retrieval","author":"J He","year":"2008","unstructured":"He, J., Larson, M., de Rijke, M.: Using coherence-based measures to predict query difficulty. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds.) ECIR 2008. LNCS, vol. 4956, pp. 689\u2013694. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-78646-7_80"},{"key":"9_CR33","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1007\/978-3-031-56063-7_27","volume-title":"ECIR 2024","author":"M Khodabakhsh","year":"2024","unstructured":"Khodabakhsh, M., Zarrinkalam, F., Arabzadeh, N.: BertPE: a BERT-based pre-retrieval estimator for query performance prediction. In: Goharian, N., et al. (eds.) ECIR 2024. LNCS, vol. 14610, pp. 354\u2013363. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-56063-7_27"},{"key":"9_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/978-3-642-23318-0_4","volume-title":"Advances in Information Retrieval Theory","author":"O Kurland","year":"2011","unstructured":"Kurland, O., Shtok, A., Carmel, D., Hummel, S.: A unified framework for post-retrieval query-performance prediction. In: Amati, G., Crestani, F. (eds.) ICTIR 2011. LNCS, vol. 6931, pp. 15\u201326. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-23318-0_4"},{"key":"9_CR35","doi-asserted-by":"crossref","unstructured":"Kurland, O., Shtok, A., Hummel, S., Raiber, F., Carmel, D., Rom, O.: Back to the roots: a probabilistic framework for query-performance prediction. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012, pp. 823\u2013832. ACM, New York (2012)","DOI":"10.1145\/2396761.2396866"},{"key":"9_CR36","doi-asserted-by":"crossref","unstructured":"Li, R., Kao, B., Bi, B., Cheng, R., Lo, E.: DQR: a probabilistic approach to diversified query recommendation. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012, pp. 16\u201325. Association for Computing Machinery, New York (2012)","DOI":"10.1145\/2396761.2396768"},{"issue":"3","key":"9_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2023.103332","volume":"60","author":"M Maistro","year":"2023","unstructured":"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)","journal-title":"Inf. Process. Manage."},{"issue":"4","key":"9_CR38","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/ijl\/3.4.235","volume":"3","author":"GA Miller","year":"1990","unstructured":"Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.J.: Introduction to wordnet: an on-line lexical database. Int. J. Lexicogr. 3(4), 235\u2013244 (1990)","journal-title":"Int. J. Lexicogr."},{"key":"9_CR39","unstructured":"Mothe, J., Tanguy, L.: Linguistic features to predict query difficulty. In: ACM Conference on Research and Development in Information Retrieval, SIGIR, Predicting Query Difficulty-Methods and Applications Workshop, pp. 7\u201310 (2005)"},{"key":"9_CR40","unstructured":"Nguyen, T., et al.: MS marco: a human generated machine reading comprehension dataset. CoRR abs\/1611.09268 (2016)"},{"key":"9_CR41","unstructured":"Patwardhan, S., Pedersen, T.: Using wordnet-based context vectors to estimate the semantic relatedness of concepts. In: Proceedings of the EACL 2006 Workshop Making Sense of Sense-Bringing Computational Linguistics and Psycholinguistics Together, vol.\u00a01501, pp.\u00a01\u20138 (2006)"},{"key":"9_CR42","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1109\/21.24528","volume":"19","author":"R Rada","year":"1989","unstructured":"Rada, R., Mili, H., Bicknell, E., Blettner, M.: Development and application of a metric on semantic nets. IEEE Trans. Syst. Man Cybern. 19, 17\u201330 (1989)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"9_CR43","doi-asserted-by":"crossref","unstructured":"Raiber, F., Kurland, O.: Query-performance prediction: setting the expectations straight. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2014, pp. 13\u201322. Association for Computing Machinery, New York (2014)","DOI":"10.1145\/2600428.2609581"},{"key":"9_CR44","doi-asserted-by":"crossref","unstructured":"Rha, E.Y., Shi, W., Belkin, N.J.: An exploration of reasons for query reformulations. In: Diversity of Engagement: Connecting People and Information in the Physical and Virtual Worlds - Proceedings of the 80th ASIS &T Annual Meeting, ASIST 2017, vol.\u00a054, pp. 337\u2013346. Wiley (2017)","DOI":"10.1002\/pra2.2017.14505401037"},{"key":"9_CR45","doi-asserted-by":"crossref","unstructured":"Roitman, H.: An enhanced approach to query performance prediction using reference lists. In: Proceedings of SIGIR 2017, pp. 869\u2013872. Association for Computing Machinery (2017)","DOI":"10.1145\/3077136.3080665"},{"key":"9_CR46","doi-asserted-by":"crossref","unstructured":"Roitman, H.: Normalized query commitment revisited. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1085\u20131088, SIGIR 2019. Association for Computing Machinery, New York (2019)","DOI":"10.1145\/3331184.3331334"},{"key":"9_CR47","doi-asserted-by":"crossref","unstructured":"Roitman, H., Erera, S., Weiner, B.: Robust standard deviation estimation for query performance prediction. In: Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2017, pp. 245\u2013248. Association for Computing Machinery, New York (2017)","DOI":"10.1145\/3121050.3121087"},{"issue":"3","key":"9_CR48","doi-asserted-by":"publisher","first-page":"1026","DOI":"10.1016\/j.ipm.2018.10.009","volume":"56","author":"D Roy","year":"2019","unstructured":"Roy, D., Ganguly, D., Mitra, M., Jones, G.J.: Estimating gaussian mixture models in the local neighbourhood of embedded word vectors for query performance prediction. Inf. Process. Manage. 56(3), 1026\u20131045 (2019)","journal-title":"Inf. Process. Manage."},{"key":"9_CR49","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1007\/978-1-4471-2099-5_15","volume-title":"SIGIR 1994","author":"M Sanderson","year":"1994","unstructured":"Sanderson, M.: Word sense disambiguation and information retrieval. In: Croft, B.W., van Rijsbergen, C.J. (eds.) SIGIR 1994, pp. 142\u2013151. Springer, London (1994). https:\/\/doi.org\/10.1007\/978-1-4471-2099-5_15"},{"key":"9_CR50","doi-asserted-by":"crossref","unstructured":"Shtok, A., Kurland, O., Carmel, D.: Using statistical decision theory and relevance models for query-performance prediction. In: Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010, pp. 259\u2013266 (2010)","DOI":"10.1145\/1835449.1835494"},{"issue":"4","key":"9_CR51","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2926790","volume":"34","author":"A Shtok","year":"2016","unstructured":"Shtok, A., Kurland, O., Carmel, D.: Query performance prediction using reference lists. ACM Trans. Inf. Syst. 34(4), 1\u201334 (2016)","journal-title":"ACM Trans. Inf. Syst."},{"issue":"2","key":"9_CR52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2180868.2180873","volume":"30","author":"A Shtok","year":"2012","unstructured":"Shtok, A., Kurland, O., Carmel, D., Raiber, F., Markovits, G.: Predicting query performance by query-drift estimation. ACM Trans. Inf. Syst. 30(2), 1\u201335 (2012)","journal-title":"ACM Trans. Inf. Syst."},{"key":"9_CR53","doi-asserted-by":"crossref","unstructured":"Tao, Y., Wu, S.: Query performance prediction by considering score magnitude and variance together. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, CIKM 2014, pp. 1891\u20131894. Association for Computing Machinery, New York (2014)","DOI":"10.1145\/2661829.2661906"},{"key":"9_CR54","doi-asserted-by":"crossref","unstructured":"Vinay, V., Cox, I.J., Milic-Frayling, N., Wood, K.R.: On ranking the effectiveness of searches. In: SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, Washington, USA, 6\u201311 August 2006, pp. 398\u2013404 (2006)","DOI":"10.1145\/1148170.1148239"},{"key":"9_CR55","doi-asserted-by":"crossref","unstructured":"Yom-Tov, E., Fine, S., Carmel, D., Darlow, A.: Learning to estimate query difficulty: including applications to missing content detection and distributed information retrieval. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 512\u2013519. ACM (2005)","DOI":"10.1145\/1076034.1076121"},{"key":"9_CR56","doi-asserted-by":"crossref","unstructured":"Zamani, H., Croft, W.B., Culpepper, J.S.: Neural query performance prediction using weak supervision from multiple signals. In: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2018, pp. 105\u2013114. Association for Computing Machinery, New York (2018)","DOI":"10.1145\/3209978.3210041"},{"key":"9_CR57","doi-asserted-by":"crossref","unstructured":"Zendel, O., Shtok, A., Raiber, F., Kurland, O., Culpepper, J.S.: Information needs, queries, and query performance prediction. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, pp. 395\u2013404. ACM, New York (2019)","DOI":"10.1145\/3331184.3331253"},{"key":"9_CR58","doi-asserted-by":"crossref","unstructured":"Zhai, C., Lafferty, J.: A study of smoothing methods for language models applied to ad hoc information retrieval. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2001, pp. 334\u2013342. Association for Computing Machinery, New York (2001)","DOI":"10.1145\/383952.384019"},{"key":"9_CR59","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1007\/978-3-540-78646-7_8","volume-title":"Advances in Information Retrieval","author":"Y Zhao","year":"2008","unstructured":"Zhao, Y., Scholer, F., Tsegay, Y.: Effective pre-retrieval query performance prediction using similarity and variability evidence. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds.) ECIR 2008. LNCS, vol. 4956, pp. 52\u201364. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-78646-7_8"},{"key":"9_CR60","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Croft, W.B.: Ranking robustness: a novel framework to predict query performance. In: Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management, Arlington, Virginia, USA, 6\u201311 November 2006, pp. 567\u2013574 (2006)","DOI":"10.1145\/1183614.1183696"},{"key":"9_CR61","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Croft, W.B.: Query performance prediction in web search environments. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007, pp. 543\u2013550. Association for Computing Machinery, New York (2007)","DOI":"10.1145\/1277741.1277835"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-88717-8_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T09:23:49Z","timestamp":1746696229000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-88717-8_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031887161","9783031887178"],"references-count":61,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-88717-8_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"3 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lucca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"47","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2025.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}