{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T10:46:22Z","timestamp":1783593982927,"version":"3.55.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Computing"],"DOI":"10.1007\/s10791-025-09683-2","type":"journal-article","created":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T15:12:05Z","timestamp":1754061125000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Ensemble learning with RAG model to reduce redundant question topics in auto-generated exam questions"],"prefix":"10.1007","volume":"28","author":[{"given":"R. Tharaniya","family":"Sairaj","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. R.","family":"Balasundaram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,1]]},"reference":[{"key":"9683_CR1","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.cogsys.2019.09.025","volume":"59","author":"O Sychev","year":"2020","unstructured":"Sychev O, Anikin A, Prokudin A. Automatic grading and hinting in open-ended text questions. Cogn Syst Res. 2020;59:264\u201372.","journal-title":"Cogn Syst Res"},{"key":"9683_CR2","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.cogsys.2021.11.002","volume":"72","author":"B Das","year":"2022","unstructured":"Das B, Majumder M, Sekh AA, Phadikar S. Automatic question generation and answer assessment for subjective examination. Cogn Syst Res. 2022;72:14\u201322.","journal-title":"Cogn Syst Res"},{"key":"9683_CR3","doi-asserted-by":"publisher","first-page":"108906","DOI":"10.1016\/j.knosys.2022.108906","volume":"249","author":"SF Kusuma","year":"2022","unstructured":"Kusuma SF, Siahaan DO, Fatichah C. Automatic question generation with various difficulty levels based on knowledge ontology using a query template. Knowl Based Syst. 2022;249:108906.","journal-title":"Knowl Based Syst"},{"issue":"11","key":"9683_CR4","doi-asserted-by":"publisher","first-page":"2220","DOI":"10.1002\/asi.22611","volume":"63","author":"QBG Cong","year":"2012","unstructured":"Cong QBG, Li C, Sun A, Chen H. An evaluation of classification models for question topic categorization. J Am Soc Inform Sci Technol. 2012;63(11):2220\u201333. https:\/\/doi.org\/10.1002\/asi.22611.","journal-title":"J Am Soc Inform Sci Technol"},{"key":"9683_CR5","doi-asserted-by":"publisher","unstructured":"Huang P-C, Chan Y-H, Yang C-Y, Chen H-Y, Fan Y-C. EQGG: automatic question group generation. IEEE Trans Learn Technol. 2024;17:1994\u20132007. https:\/\/doi.org\/10.1109\/TLT.2024.3430225.","DOI":"10.1109\/TLT.2024.3430225"},{"key":"9683_CR6","doi-asserted-by":"publisher","unstructured":"Tomikawa Y, Suzuki A, Uto M. Adaptive question\u2013answer generation with difficulty control using item response theory and pretrained transformer models. IEEE Trans Learn Techno. 2025;17:2186\u201398. https:\/\/doi.org\/10.1109\/TLT.2024.3491801","DOI":"10.1109\/TLT.2024.3491801"},{"key":"9683_CR7","doi-asserted-by":"publisher","unstructured":"Chung H-L, Chan Y-H, Fan Y-C. Handover QG: question generation by decoder fusion and reinforcement learning. IEEE\/ACM Trans Audio Speech Lang Process. 2024;32:3644\u201355. https:\/\/doi.org\/10.1109\/TASLP.2024.3426292.","DOI":"10.1109\/TASLP.2024.3426292"},{"key":"9683_CR8","doi-asserted-by":"publisher","unstructured":"Willis A, Davis G, Ruan S, Manoharan L, Landay J, Brunskill E. Key phrase extraction for generating educational question-answer pairs. In: Proceedings of the 2019 ACM SIGCHI Conference on Human Factors in Computing Systems. 2019. pp. 1\u201310. https:\/\/doi.org\/10.1145\/3330430.3333636.","DOI":"10.1145\/3330430.3333636"},{"key":"9683_CR9","unstructured":"Lewis P, Perez E, Piktus A, Petroni F, Karpukhin V, Goyal N, Kiela D. Retrieval-augmented generation for knowledge-intensive nlp tasks. Adv Neural Inform Process Syst. 2020;33:9459\u201374."},{"key":"9683_CR10","doi-asserted-by":"crossref","unstructured":"Anand A, Goel A, Hira M, Buldeo S, Kumar J, Verma A, Gupta R, Shah RR. SciPhyRAG-Retrieval augmentation to improve LLMs on physics Q&A. In: International Conference on Big Data Analytics. 2023. pp. 50\u201363.","DOI":"10.1007\/978-3-031-49601-1_4"},{"key":"9683_CR11","doi-asserted-by":"publisher","first-page":"103642","DOI":"10.1016\/j.compedu.2019.103642","volume":"142","author":"G George","year":"2019","unstructured":"George G, Lal AM. Review of ontology-based recommender systems in e-learning. Comput Educ. 2019;142:103642.","journal-title":"Comput Educ"},{"key":"9683_CR12","doi-asserted-by":"publisher","first-page":"105508","DOI":"10.1016\/j.knosys.2020.105508","volume":"194","author":"SD Cardoso","year":"2020","unstructured":"Cardoso SD, Silveira D, M., Pruski C. Construction and exploitation of an historical knowledge graph to deal with the evolution of ontologies. Knowl Based Syst. 2020;194:105508.","journal-title":"Knowl Based Syst"},{"key":"9683_CR13","doi-asserted-by":"publisher","first-page":"120694","DOI":"10.1016\/j.eswa.2023.120694","volume":"231","author":"Jianrui","year":"2023","unstructured":"Jianrui, Yang L. Subgraph-aware virtual node matching graph attention network for entity alignment. Expert Syst Appl. 2023;231:120694. https:\/\/doi.org\/10.1016\/j.eswa.2023.120694.","journal-title":"Expert Syst Appl"},{"key":"9683_CR14","doi-asserted-by":"publisher","first-page":"122191","DOI":"10.1016\/j.eswa.2023.122191","volume":"238","author":"X Zhang","year":"2024","unstructured":"Zhang X, Zhang J, Fu X. A viewpoint adaptation ensemble contrastive learning framework for vessel type recognition with limited data. Expert Syst Appl. 2024;238:122191. https:\/\/doi.org\/10.1016\/j.eswa.2023.122191.","journal-title":"Expert Syst Appl"},{"key":"9683_CR15","doi-asserted-by":"crossref","unstructured":"Sun K, Yu J, Li J, Hou L. Exploring sequence-to-sequence taxonomy expansion via Language model probing. Expert Syst Appl. 2023;122321.","DOI":"10.1016\/j.eswa.2023.122321"},{"key":"9683_CR16","unstructured":"Dataset MAMO. https:\/\/bioportal.bioontology.org\/ontologies\/MAMO. Accessed 24 Nov 2023."},{"key":"9683_CR17","unstructured":"Dataset ODT. https:\/\/bioportal.bioontology.org\/ontologies\/ONTODT. Accessed 24 Nov 2023."},{"key":"9683_CR18","unstructured":"Dataset DCO. https:\/\/bioportal.bioontology.org\/ontologies\/GDCO. Accessed 24 Nov 2023."},{"key":"9683_CR19","doi-asserted-by":"publisher","first-page":"139197","DOI":"10.1016\/j.scitotenv.2020.139197","volume":"730","author":"S Saha","year":"2020","unstructured":"Saha S, Saha M, Mukherjee K, Arabameri A, Ngo PTT, Paul GC. Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, reptree: A case study at the Gumani river basin, India. Sci Total Environ. 2020;730:139197.","journal-title":"Sci Total Environ"},{"key":"9683_CR20","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.future.2021.04.015","volume":"123","author":"A Assi","year":"2021","unstructured":"Assi A, Dhifli W. Instance matching in knowledge graphs through random walks and semantics. Future Generation Comput Syst. 2021;123:73\u201384.","journal-title":"Future Generation Comput Syst"},{"key":"9683_CR21","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.ins.2021.02.018","volume":"564","author":"E Amador-Dominguez","year":"2021","unstructured":"Amador-Dominguez E, Serrano E, Manrique D, Hohenecker P, Lukasiewicz T. An ontology-based deep learning approach for triple classification with out-of-knowledge-base entities. Inf Sci. 2021;564:85\u2013102.","journal-title":"Inf Sci"},{"key":"9683_CR22","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.inffus.2021.01.007","volume":"71","author":"I Osman","year":"2021","unstructured":"Osman I, Yahia SB, Diallo G. Ontology integration: approaches and challenging issues. Inform Fusion. 2021;71:38\u201363.","journal-title":"Inform Fusion"},{"issue":"140","key":"9683_CR23","first-page":"1","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Liu PJ. Exploring the limits of transfer learning with a unified text-to-text transformer. J Mach Learn Res. 2020;21(140):1\u201367.","journal-title":"J Mach Learn Res"},{"key":"9683_CR24","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1016\/j.ins.2020.08.069","volume":"547","author":"F Jiang","year":"2021","unstructured":"Jiang F, Yu X, Du J, Gong D, Zhang Y, Peng Y. Ensemble learning based on approximate reducts and bootstrap sampling. Inf Sci. 2021;547:797\u2013813. https:\/\/doi.org\/10.1016\/j.ins.2020.08.069.","journal-title":"Inf Sci"},{"key":"9683_CR25","doi-asserted-by":"publisher","first-page":"102310","DOI":"10.1016\/j.is.2023.102310","volume":"120","author":"FA Khalifa","year":"2024","unstructured":"Khalifa FA, Abdelkader HM, Elsaid AH. An analysis of ensemble pruning methods under the explanation of random forest. Inform Syst. 2024;120:102310. https:\/\/doi.org\/10.1016\/j.is.2023.102310.","journal-title":"Inform Syst"},{"key":"9683_CR26","doi-asserted-by":"publisher","first-page":"125919","DOI":"10.1016\/j.eswa.2024.125919","volume":"264","author":"F Jiang","year":"2025","unstructured":"Jiang F, Hu Q, Yang Z, Liu J, Du J. A neighborhood rough sets-based ensemble method, with application to software fault prediction. Expert Syst Appl. 2025;264:125919. https:\/\/doi.org\/10.1016\/j.eswa.2024.125919.","journal-title":"Expert Syst Appl"},{"key":"9683_CR27","doi-asserted-by":"publisher","first-page":"120239","DOI":"10.1016\/j.eswa.2023.120239","volume":"228","author":"J Rodr\u00edguez-Revello","year":"2023","unstructured":"Rodr\u00edguez-Revello J, Barba-Gonz\u00e1lez C, Rybinski M, Navas-Delgado I. KNIT: ontology reusability through knowledge graph exploration. Expert Syst Appl. 2023;228:120239.","journal-title":"Expert Syst Appl"},{"key":"9683_CR28","doi-asserted-by":"publisher","first-page":"105248","DOI":"10.1016\/j.cageo.2022.105248","volume":"170","author":"G Sarailidis","year":"2023","unstructured":"Sarailidis G, Wagener T, Pianosi F. Integrating scientific knowledge into machine learning using interactive decision trees. Comput Geosci. 2023;170:105248.","journal-title":"Comput Geosci"},{"key":"9683_CR29","doi-asserted-by":"publisher","first-page":"100472","DOI":"10.1016\/j.websem.2018.09.003","volume":"57","author":"A Alobaid","year":"2019","unstructured":"Alobaid A, Garijo D, Poveda-Villal\u00f3n M, Santana-Perez I, Fern\u00e1ndez-Izquierdo A, Corcho O. Automating ontology engineering support activities with ontoology. J Web Semant. 2019;57:100472.","journal-title":"J Web Semant"},{"key":"9683_CR30","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.catena.2018.12.018","volume":"175","author":"BT Pham","year":"2019","unstructured":"Pham BT, Prakash I, Singh SK, Shirzadi A, Shahabi H, Bui DT. Landslide susceptibility modeling using reduced error pruning trees and different ensemble techniques: hybrid machine learning approaches. CATENA. 2019;175:203\u201318.","journal-title":"CATENA"},{"key":"9683_CR31","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.eswa.2019.03.018","volume":"127","author":"C Iorio","year":"2019","unstructured":"Iorio C, Aria M, D\u2019Ambrosio A, Siciliano R. Informative trees by visual pruning. Expert Syst Appl. 2019;127:228\u201340.","journal-title":"Expert Syst Appl"},{"key":"9683_CR32","unstructured":"Dataset DPO. https:\/\/bioportal.bioontology.org\/ontologies\/ONL-DP. Accessed 24 Nov 2023."},{"key":"9683_CR33","doi-asserted-by":"publisher","first-page":"100487","DOI":"10.1016\/j.websem.2018.12.005","volume":"57","author":"ACB Garcia","year":"2019","unstructured":"Garcia ACB, Vivacqua AS. Grounding knowledge acquisition with ontology explanation: A case study. J Web Semant. 2019;57:100487.","journal-title":"J Web Semant"},{"key":"9683_CR34","unstructured":"Dataset ODM. https:\/\/bioportal.bioontology.org\/ontologies\/ONTODM-CORE. Accessed 24 Nov 2023."}],"container-title":["Discover Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10791-025-09683-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10791-025-09683-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10791-025-09683-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T11:25:02Z","timestamp":1757330702000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10791-025-09683-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,1]]},"references-count":34,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["9683"],"URL":"https:\/\/doi.org\/10.1007\/s10791-025-09683-2","relation":{},"ISSN":["2948-2992"],"issn-type":[{"value":"2948-2992","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,1]]},"assertion":[{"value":"19 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethics approval and consent to participate were not applicable as this research did not involve human or animal participants.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Consent for publication is not applicable as this manuscript does not include data from individuals.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"161"}}