{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:09:44Z","timestamp":1774310984098,"version":"3.50.1"},"publisher-location":"Cham","reference-count":64,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032213204","type":"print"},{"value":"9783032213211","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-21321-1_57","type":"book-chapter","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T11:08:42Z","timestamp":1774264122000},"page":"528-543","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating the\u00a0Efficiency and\u00a0Effectiveness of\u00a0Learned Sparse Retrieval with\u00a0the\u00a0lsr_benchmark"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1003-981X","authenticated-orcid":false,"given":"Maik","family":"Fr\u00f6be","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6032-909X","authenticated-orcid":false,"given":"Ferdinand","family":"Schlatt","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0194-361X","authenticated-orcid":false,"given":"Cosimo","family":"Rulli","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4854-7249","authenticated-orcid":false,"given":"Tim","family":"Hagen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1992-8696","authenticated-orcid":false,"given":"Jan Heinrich","family":"Merker","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0945-3148","authenticated-orcid":false,"given":"Gijs","family":"Hendriksen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7754-6656","authenticated-orcid":false,"given":"Carlos","family":"Lassance","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3183-334X","authenticated-orcid":false,"given":"Franco Maria","family":"Nardini","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9830-3936","authenticated-orcid":false,"given":"Rossano","family":"Venturini","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2451-0665","authenticated-orcid":false,"given":"Martin","family":"Potthast","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,24]]},"reference":[{"key":"57_CR1","doi-asserted-by":"crossref","unstructured":"Abualsaud, M., Lioma, C., Maistro, M., Smucker, M.D., Zuccon, G.: Overview of the TREC 2019 decision track. In: Proceedings of TREC 2019 (2019)","DOI":"10.6028\/NIST.SP.1250.decisions-UWaterlooMDS"},{"key":"57_CR2","doi-asserted-by":"crossref","unstructured":"Breuer, T., Keller, J., Schaer, P.: ir_metadata: an extensible metadata schema for IR experiments. In: Proceedings of SIGIR 2022, pp. 3078\u20133089, ACM (2022)","DOI":"10.1145\/3477495.3531738"},{"key":"57_CR3","doi-asserted-by":"crossref","unstructured":"Broder, A.Z., Carmel, D., Herscovici, M., Soffer, A., Zien, J.: Efficient query evaluation using a two-level retrieval process. In: Proceedings of CIKM 2003, pp. 426\u2013434 (2003)","DOI":"10.1145\/956863.956944"},{"key":"57_CR4","doi-asserted-by":"crossref","unstructured":"Bruch, S., Fr\u00f6be, M., Hagen, T., Nardini, F.M., Potthast, M.: Reneuir at SIGIR 2025: The fourth workshop on reaching efficiency in neural information retrieval. In: Proceedings of SIGIR 2025, pp. 4153\u20134156, ACM (2025)","DOI":"10.1145\/3726302.3730358"},{"key":"57_CR5","doi-asserted-by":"crossref","unstructured":"Bruch, S., Lucchese, C., Nardini, F.M.: Reneuir: Reaching efficiency in neural information retrieval. In: Proceedings of SIGIR 2022, p. 3462\u20133465, ACM (2022)","DOI":"10.1145\/3477495.3531704"},{"key":"57_CR6","doi-asserted-by":"crossref","unstructured":"Bruch, S., Mackenzie, J., Maistro, M., Nardini, F.M.: Reneuir at SIGIR 2023: The second workshop on reaching efficiency in neural information retrieval. In: Proceedings of SIGIR 2023, pp. 3456\u20133459, ACM (2023)","DOI":"10.1145\/3539618.3591922"},{"key":"57_CR7","doi-asserted-by":"crossref","unstructured":"Bruch, S., Nardini, F.M., Rulli, C., Venturini, R.: Efficient inverted indexes for approximate retrieval over learned sparse representations. In: Proceedings of SIGIR 2024, pp. 152\u2013162 (2024)","DOI":"10.1145\/3626772.3657769"},{"key":"57_CR8","doi-asserted-by":"crossref","unstructured":"Bruch, S., Nardini, F.M., Rulli, C., Venturini, R.: Pairing clustered inverted indexes with knn graphs for fast approximate retrieval over learned sparse representations. In: Proceedings of CIKM 2024 (2024)","DOI":"10.1145\/3627673.3679977"},{"key":"57_CR9","doi-asserted-by":"crossref","unstructured":"Bruch, S., Nardini, F.M., Rulli, C., Venturini, R., Venuta, L.: Investigating the scalability of approximate sparse retrieval algorithms to massive datasets. In: Proceedings of ECIR 2025, pp. 437\u2013445 (2025)","DOI":"10.1007\/978-3-031-88714-7_43"},{"key":"57_CR10","doi-asserted-by":"crossref","unstructured":"Catena, M., Frieder, O., Tonellotto, N.: Efficient energy management in distributed web search. In: Proceedings of CIKM 2018, pp. 1555\u20131558, ACM (2018)","DOI":"10.1145\/3269206.3269263"},{"key":"57_CR11","doi-asserted-by":"crossref","unstructured":"Catena, M., Macdonald, C., Tonellotto, N.: Load-sensitive CPU power management for web search engines. In: Proceedings of SIGIR 2015, pp. 751\u2013754, ACM (2015)","DOI":"10.1145\/2766462.2767809"},{"key":"57_CR12","doi-asserted-by":"crossref","unstructured":"Chen, J., Xiao, S., Zhang, P., Luo, K., Lian, D., Liu, Z.: Bge m3-embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation. arXiv preprint arXiv:2402.03216 (2024)","DOI":"10.18653\/v1\/2024.findings-acl.137"},{"key":"57_CR13","doi-asserted-by":"crossref","unstructured":"Clarke, C.L.A., Craswell, N., Soboroff, I.: Overview of the TREC\u00a02009 Web track. In: Proceedings of TREC 2009, NIST (2009)","DOI":"10.6028\/NIST.SP.500-278.web-overview"},{"key":"57_CR14","doi-asserted-by":"crossref","unstructured":"Clarke, C.L.A., Craswell, N., Soboroff, I., Cormack, G.V.: Overview of the TREC\u00a02010 Web track. In: Proceedings of TREC 2010, NIST (2010)","DOI":"10.6028\/NIST.SP.500-294.web-overview"},{"key":"57_CR15","doi-asserted-by":"crossref","unstructured":"Clarke, C.L.A., Craswell, N., Soboroff, I., Voorhees, E.M.: Overview of the TREC\u00a02011 Web track. In:Proceedings of TREC 2011, NIST (2011)","DOI":"10.6028\/NIST.SP.500-296.web-overview"},{"key":"57_CR16","doi-asserted-by":"crossref","unstructured":"Clarke, C.L.A., Craswell, N., Voorhees, E.M.: Overview of the TREC\u00a02012 Web track. In: Proceedings of TREC 2012, NIST (2012)","DOI":"10.6028\/NIST.SP.500-298.web-overview"},{"key":"57_CR17","doi-asserted-by":"crossref","unstructured":"Collins-Thompson, K., Bennett, P.N., Diaz, F., Clarke, C., Voorhees, E.M.: TREC\u00a02013 Web track overview. In: Proceedings of TREC 2013, NIST (2013)","DOI":"10.6028\/NIST.SP.500-302.web-overview"},{"key":"57_CR18","doi-asserted-by":"crossref","unstructured":"Collins-Thompson, K., Macdonald, C., Bennett, P.N., Diaz, F., Voorhees, E.M.: TREC\u00a02014 Web track overview. In: Proceedings of TREC 2014, NIST (2014)","DOI":"10.6028\/NIST.SP.500-308.web-overview"},{"key":"57_CR19","unstructured":"Courty, B.: mlco2\/codecarbon: v2.4.1 (May 2024). https:\/\/doi.org\/10.5281\/zenodo.11171501"},{"key":"57_CR20","doi-asserted-by":"crossref","unstructured":"Craswell, N., Mitra, B., Yilmaz, E., Campos, D.: Overview of the TREC\u00a02020 Deep Learning Track. In: Proceedings of TREC 2020, NIST (2020)","DOI":"10.6028\/NIST.SP.1266.deep-overview"},{"key":"57_CR21","doi-asserted-by":"crossref","unstructured":"Craswell, N., Mitra, B., Yilmaz, E., Campos, D., Voorhees, E.M.: Overview of the TREC\u00a02019 Deep Learning Track. In: Proceedings of TREC 2019, NIST (2019)","DOI":"10.6028\/NIST.SP.1266.deep-overview"},{"key":"57_CR22","doi-asserted-by":"crossref","unstructured":"Delfino, L., Erriquez, D., Martinico, S., Nardini, F.M., Rulli, C., Venturini, R.: kannolo: Sweet and smooth approximate k-nearest neighbors search. In: Proceedings of ECIR 2025, pp. 400\u2013406 (2025)","DOI":"10.1007\/978-3-031-88717-8_29"},{"key":"57_CR23","doi-asserted-by":"crossref","unstructured":"Ding, S., Suel, T.: Faster top-k document retrieval using block-max indexes. In: Proceedings of SIGIR 2011, pp. 993\u20131002, ACM (2011)","DOI":"10.1145\/2009916.2010048"},{"issue":"1","key":"57_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3687273.3687290","volume":"58","author":"SM Farzana","year":"2024","unstructured":"Farzana, S.M., et al.: Report on the 1st international workshop on open web search (WOWS 2024) at ECIR 2024. SIGIR Forum 58(1), 1\u201313 (2024)","journal-title":"SIGIR Forum"},{"key":"57_CR25","doi-asserted-by":"crossref","unstructured":"Farzana, S.M., et al.: The first international workshop on open web search (WOWS). In: Proceedings of ECIR 2024, LNCS, vol. 14612, pp. 426\u2013431, Springer (2024)","DOI":"10.1007\/978-3-031-56069-9_58"},{"key":"57_CR26","doi-asserted-by":"crossref","unstructured":"Formal, T., Lassance, C., Piwowarski, B., Clinchant, S.: Splade v2: Sparse lexical and expansion model for information retrieval (2021)","DOI":"10.1145\/3404835.3463098"},{"key":"57_CR27","doi-asserted-by":"crossref","unstructured":"Formal, T., Piwowarski, B., Clinchant, S.: Splade: Sparse lexical and expansion model for first stage ranking. In: Proceedings of SIGIR 2021, pp. 2288\u20132292 (2021)","DOI":"10.1145\/3404835.3463098"},{"key":"57_CR28","doi-asserted-by":"crossref","unstructured":"Fr\u00f6be, M., Mackenzie, J., Mitra, B., Nardini, F.M., Potthast, M.: ReNeuIR at SIGIR\u00a02024: The third workshop on reaching efficiency in neural information retrieval. In: Proceedings of SIGIR 2024, pp. 3051\u20133054, ACM (2024)","DOI":"10.1145\/3626772.3657994"},{"key":"57_CR29","doi-asserted-by":"crossref","unstructured":"Fr\u00f6be, M., et al.: Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora. In: Proceedings of ECIR 2025, pp. 453\u2013471, LNCS, Springer (2025)","DOI":"10.1007\/978-3-031-88708-6_29"},{"key":"57_CR30","doi-asserted-by":"crossref","unstructured":"Fr\u00f6be, M., et al.: The information retrieval experiment platform. In: Proceedings of SIGIR 2023, pp. 2826\u20132836, ACM (2023)","DOI":"10.1145\/3539618.3591888"},{"key":"57_CR31","doi-asserted-by":"crossref","unstructured":"Fr\u00f6be, M., et al.: Continuous integration for reproducible shared tasks with TIRA.io. In: Proceedings of ECIR 2023, pp. 236\u2013241, LNCS, Springer (2023)","DOI":"10.1007\/978-3-031-28241-6_20"},{"key":"57_CR32","unstructured":"Geng, Z., Wang, Y., Ru, D., Yang, Y.: Towards competitive search relevance for inference-free learned sparse retrievers (2025)"},{"key":"57_CR33","doi-asserted-by":"crossref","unstructured":"Hagen, T., Fr\u00f6be, M., Merker, J.H., Scells, H., Hagen, M., Potthast, M.: Tirex tracker: The information retrieval experiment tracker. In: Proceedings of SIGIR 2025, pp. 3764\u20133771, ACM (2025)","DOI":"10.1145\/3726302.3730297"},{"key":"57_CR34","doi-asserted-by":"crossref","unstructured":"Khandel, P., Yates, A., Varbanescu, A.L., de\u00a0Rijke, M., Pimentel, A.D.: PEIR: modeling performance in neural information retrieval. In: Proceedings of ECIR 2025, pp. 279\u2013294, LNCS, Springer (2025)","DOI":"10.1007\/978-3-031-88711-6_18"},{"key":"57_CR35","unstructured":"Lassance, C., D\u00e9jean, H., Formal, T., Clinchant, S.: Splade-v3: New baselines for splade (Mar 2024)"},{"key":"57_CR36","doi-asserted-by":"crossref","unstructured":"Lawrie, D.J., Kayi, E.S., Yang, E., Mayfield, J., Oard, D.W.: PLAID SHIRTTT for large-scale streaming dense retrieval. In: Proceedings of SIGIR 2024, pp. 2574\u20132578, ACM (2024)","DOI":"10.1145\/3626772.3657964"},{"key":"57_CR37","unstructured":"Lin, J., Ma, X.: A few brief notes on deepimpact, coil, and a conceptual framework for information retrieval techniques (Jun 2021)"},{"key":"57_CR38","doi-asserted-by":"crossref","unstructured":"Lin, J., Ma, X., Lin, S., Yang, J., Pradeep, R., Nogueira, R.: Pyserini: a python toolkit for reproducible information retrieval research with sparse and dense representations. In: Proceedings of SIGIR 2021, pp. 2356\u20132362, ACM (2021)","DOI":"10.1145\/3404835.3463238"},{"key":"57_CR39","doi-asserted-by":"crossref","unstructured":"MacAvaney, S., Yates, A., Feldman, S., Downey, D., Cohan, A., Goharian, N.: Simplified data wrangling with ir_datasets. In: Proceedings of SIGIR 2021, pp. 2429\u20132436, ACM (2021)","DOI":"10.1145\/3404835.3463254"},{"key":"57_CR40","doi-asserted-by":"crossref","unstructured":"Macdonald, C., Tonellotto, N., MacAvaney, S., Ounis, I.: PyTerrier: Declarative experimentation in Python from BM25 to dense retrieval. In: Proceedings of CIKM 2021, pp. 4526\u20134533, ACM (2021)","DOI":"10.1145\/3459637.3482013"},{"key":"57_CR41","doi-asserted-by":"crossref","unstructured":"Mackenzie, J., Mallia, A., Moffat, A., Petri, M.: Accelerating learned sparse indexes via term impact decomposition. In: Proceedings of EMNLP 2022, pp. 2830\u20132842 (2022)","DOI":"10.18653\/v1\/2022.findings-emnlp.205"},{"key":"57_CR42","unstructured":"Mackenzie, J., Trotman, A., Lin, J.: Wacky weights in learned sparse representations and the revenge of score-at-a-time query evaluation (Oct 2021)"},{"key":"57_CR43","doi-asserted-by":"crossref","unstructured":"Mallia, A., Mackenzie, J., Suel, T., Tonellotto, N.: Faster learned sparse retrieval with guided traversal. In: Proceedings of SIGIR 2022, pp. 1901\u20131905 (2022)","DOI":"10.1145\/3477495.3531774"},{"key":"57_CR44","doi-asserted-by":"crossref","unstructured":"Mallia, A., Ottaviano, G., Porciani, E., Tonellotto, N., Venturini, R.: Faster blockmax WAND with variable-sized blocks. In: Proceedings of SIGIR 2017, pp. 625\u2013634, ACM (2017)","DOI":"10.1145\/3077136.3080780"},{"key":"57_CR45","unstructured":"Mallia, A., Siedlaczek, M., Mackenzie, J., Suel, T.: PISA: performant indexes and search for academia. In: Proceedings of OSIRRC@SIGIR 2019, pp. 50\u201356 (2019)"},{"key":"57_CR46","doi-asserted-by":"crossref","unstructured":"Nardini, F.M., Nguyen, T., Rulli, C., Venturini, R., Yates, A.: Effective inference-free retrieval for learned sparse representations. In: Proceedings of SIGIR 2025, pp. 2936\u20132940 (2025)","DOI":"10.1145\/3726302.3730185"},{"key":"57_CR47","doi-asserted-by":"crossref","unstructured":"Nguyen, T., MacAvaney, S., Yates, A.: A unified framework for learned sparse retrieval. In: Proceedings of ECIR 2023, pp. 101\u2013116 (Apr 2023)","DOI":"10.1007\/978-3-031-28241-6_7"},{"key":"57_CR48","doi-asserted-by":"crossref","unstructured":"Qiao, Y., Yang, Y., He, S., Yang, T.: Representation sparsification with hybrid thresholding for fast splade-based document retrieval. In: Proceedings of SIGIR 2023, pp. 2329\u20132333 (2023)","DOI":"10.1145\/3539618.3592051"},{"key":"57_CR49","doi-asserted-by":"crossref","unstructured":"Raasveldt, M., M\u00fchleisen, H.: Duckdb: an embeddable analytical database. In: Proceedings of SIGMOD 2019, pp. 1981\u20131984, ACM (2019)","DOI":"10.1145\/3299869.3320212"},{"key":"57_CR50","doi-asserted-by":"crossref","unstructured":"Robertson, S.E., Walker, S., Jones, S., Hancock-Beaulieu, M., Gatford, M.: Okapi at trec-3. In: Proceedings of TREC 1994, NIST (1994)","DOI":"10.6028\/NIST.SP.500-225.adhoc-city"},{"key":"57_CR51","unstructured":"Sanh, V., Debut, L., Chaumond, J., Wolf, T.: Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter (Mar 2020)"},{"key":"57_CR52","doi-asserted-by":"crossref","unstructured":"Scells, H., Zhuang, S., Zuccon, G.: Reduce, reuse, recycle: Green information retrieval research. In: Proceedings of SIGIR 2022, pp. 2825\u20132837 (2022)","DOI":"10.1145\/3477495.3531766"},{"key":"57_CR53","doi-asserted-by":"crossref","unstructured":"Schlatt, F., Fr\u00f6be, M., Hagen, M.: Lightning IR: straightforward fine-tuning and inference of transformer-based language models for information retrieval. In: Proceedings of WSDM 2025, pp. 1048\u20131051, ACM (2025)","DOI":"10.1145\/3701551.3704118"},{"key":"57_CR54","doi-asserted-by":"crossref","unstructured":"Shen, X., Geng, Z., Yang, Y.: Exploring $$\\${\\backslash }\\rm ell_0\\$$$ sparsification for inference-free sparse retrievers. In: Proceedings of SIGIR 2025, pp. 2572\u20132576 (2025)","DOI":"10.1145\/3726302.3730192"},{"issue":"1","key":"57_CR55","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1108\/eb026526","volume":"28","author":"K Sparck Jones","year":"1972","unstructured":"Sparck Jones, K.: A statistical interpretation of term specificity and its application in retrieval. J. Doc. 28(1), 11\u201321 (1972)","journal-title":"J. Doc."},{"key":"57_CR56","doi-asserted-by":"crossref","unstructured":"Strubell, E., Ganesh, A., McCallum, A.: Energy and policy considerations for deep learning in NLP. In: Proceedings of ACL 2019, pp. 3645\u20133650, ACL (2019)","DOI":"10.18653\/v1\/P19-1355"},{"issue":"6","key":"57_CR57","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1016\/0306-4573(95)00020-H","volume":"31","author":"H Turtle","year":"1995","unstructured":"Turtle, H., Flood, J.: Query evaluation: strategies and optimizations. Inform. Process. Manage. 31(6), 831\u2013850 (1995)","journal-title":"Inform. Process. Manage."},{"key":"57_CR58","unstructured":"Upadhyay, S., et al.: A large-scale study of relevance assessments with large language models: An initial look. CoRR abs\/2411.08275 (2024)"},{"key":"57_CR59","doi-asserted-by":"crossref","unstructured":"Voorhees, E.M.: The philosophy of information retrieval evaluation. In: Proceedings of CLEF 2001, LNCS, vol. 2406, pp. 355\u2013370, Springer (2001)","DOI":"10.1007\/3-540-45691-0_34"},{"key":"57_CR60","doi-asserted-by":"crossref","unstructured":"Voorhees, E.M.: Overview of the TREC\u00a02004 Robust track. In: Proceedings of TREC 2004, NIST (2004)","DOI":"10.6028\/NIST.SP.500-261.robust-overview"},{"key":"57_CR61","doi-asserted-by":"crossref","unstructured":"Voorhees, E.M.: The evolution of cranfield. In: Proceedings of CLEF 2019, pp. 45\u201369, Springer (2019)","DOI":"10.1007\/978-3-030-22948-1_2"},{"key":"57_CR62","doi-asserted-by":"crossref","unstructured":"Xiao, S., Liu, Z., Zhang, P., Muennighoff, N., Lian, D., Nie, J.Y.: C-pack: Packaged resources to advance general chinese embedding (May 2024)","DOI":"10.1145\/3626772.3657878"},{"key":"57_CR63","doi-asserted-by":"crossref","unstructured":"Yang, P., Fang, H., Lin, J.: Anserini: enabling the use of Lucene for information retrieval research. In: Proceedings of SIGIR 2017, pp. 1253\u20131256, ACM (2017)","DOI":"10.1145\/3077136.3080721"},{"key":"57_CR64","doi-asserted-by":"crossref","unstructured":"Zamani, H., Dehghani, M., Croft, W.B., Learned-Miller, E., Kamps, J.: From neural re-ranking to neural ranking: Learning a sparse representation for inverted indexing. In: Proceedings of CIKM 2018, pp. 497\u2013506 (2018)","DOI":"10.1145\/3269206.3271800"}],"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\/978-3-032-21321-1_57","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T23:15:09Z","timestamp":1774307709000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-21321-1_57"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032213204","9783032213211"],"references-count":64,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-21321-1_57","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"24 March 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"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":"Delft","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 March 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 April 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"48","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2026.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}