{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T12:11:14Z","timestamp":1790079074023,"version":"4.0.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,3]],"date-time":"2026-05-03T00:00:00Z","timestamp":1777766400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":142,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]},{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]},{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]},{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]},{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]},{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]},{"name":"NIH-NIAID","award":["U24AI171008."],"award-info":[{"award-number":["U24AI171008."]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Biomed Semant"],"DOI":"10.1186\/s13326-026-00353-w","type":"journal-article","created":{"date-parts":[[2026,5,3]],"date-time":"2026-05-03T03:12:55Z","timestamp":1777777975000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["BERTopic-driven term extraction from biomedical texts toward ontology population: evaluating vaccine ontology with Plotkin\u2019s vaccines corpus"],"prefix":"10.1186","volume":"17","author":[{"given":"B. Damayanthi","family":"Jesudas","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sam","family":"Smith","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng-Yu","family":"Yeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Beverley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William D.","family":"Duncan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongqun","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,3]]},"reference":[{"issue":"Suppl 2","key":"353_CR1","doi-asserted-by":"publisher","first-page":"S8","DOI":"10.1186\/2041-1480-2-S2-S8","volume":"2","author":"A Ozg\u00fcr","year":"2011","unstructured":"Ozg\u00fcr A, Xiang Z, Radev DR, He Y. Mining of vaccine-associated IFN-\u03b3 gene interaction networks using the Vaccine Ontology. J Biomedical Semant. 2011;2(Suppl 2):S8.","journal-title":"J Biomedical Semant"},{"key":"353_CR2","doi-asserted-by":"crossref","unstructured":"Zheng J, Lin AL, Huffman A, Masci AM, Racz R, Wu G, Roan K, Ong E, Sarntivijai S, Hu J, Asfaw E, Kahn H, Li X, Zhang X, Monickaraj J, Kosar N, Li J, Manuel W, Abeysinghe R, Rehana H, Bansal B, Pan P, Guo J, He V, Song J, Seleznev A, Hur K, He A, Davydov A, Yang Q, Ostropolets A, Vita R, Peters B, Ruttenberg A, Diehl A, Hoyt C, Roncaglia P, Huntley R, Scheuermann R, Courtot M, Todd T, Sayers S, Chen F, Li X, Yeh F, Xiang Z, Ozgur A, Whetzel P, Musen M, Mungall C, Leitner W, Cui L, Colby L, Mobley H, Athey B, Omenn G, Cowell L, Cui T, Hur J, Smith B, He Y. VO: The Vaccine Ontology. Sci Data. 2026.","DOI":"10.1101\/2025.08.12.669998"},{"issue":"1","key":"353_CR3","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1186\/2041-1480-3-17","volume":"3","author":"Y Lin","year":"2012","unstructured":"Lin Y, He Y. Ontology representation and analysis of vaccine formulation and administration and their effects on vaccine immune responses. J Biomedical Semant. 2012;3(1):17.","journal-title":"J Biomedical Semant"},{"key":"353_CR4","doi-asserted-by":"crossref","unstructured":"Sahbi A, Alec C, Beust P. Automatic ontology population from textual advertisements: LLM vs. semantic approach. Procedia Computer Science, 246, 3083\u20133092. Proceedings of the 28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2024). Elsevier. 2024.","DOI":"10.1016\/j.procs.2024.09.364"},{"key":"353_CR5","unstructured":"N\u00e9dellec C, Nazarenko A. Ontologies and information extraction. arXiv preprint cs\/0609137. 2006."},{"key":"353_CR6","doi-asserted-by":"crossref","unstructured":"Zhang Z, Ciravegna F. Named entity recognition for ontology population using background knowledge from Wikipedia. In: Ontology learning and knowledge discovery using the web: challenges and recent advances. IGI Global; 2011:79\u2013104.","DOI":"10.4018\/978-1-60960-625-1.ch005"},{"key":"353_CR7","doi-asserted-by":"crossref","unstructured":"Muhammad I, Kearney A, Gamble C, Coenen F, Williamson P. Open information extraction for knowledge graph construction, In: Database and Expert Systems Applications: DEXA 2020 International Workshops BIOKDD, IWCFS and MLKgraphs, Bratislava, Slovakia, September 14\u201317, 2020, Proceedings 31, Springer.","DOI":"10.1007\/978-3-030-59028-4_10"},{"key":"353_CR8","doi-asserted-by":"crossref","unstructured":"Boer VD, Someren M, Wielinga B. Relation instantiation for ontology population using the web, 2006:202\u201313.","DOI":"10.1007\/978-3-540-69912-5_16"},{"key":"353_CR9","doi-asserted-by":"crossref","unstructured":"Imsombut A, Sirikayon C. An alternative technique for populating Thai tourism ontology from texts based on machine learning. In 2016 IEEE\/ACIS 15th International Conference on Computer and Information Science (ICIS) . IEEE; 2016. p. 1-4.","DOI":"10.1109\/ICIS.2016.7550762"},{"key":"353_CR10","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1016\/j.procs.2019.09.212","volume":"159","author":"A Ayadi","year":"2019","unstructured":"Ayadi A, Samet A, d. B. de Beuvron F, Zanni-Merk C. Ontology population with deep learning-based NLP: A case study on the biomolecular network ontology. Procedia Comput Sci. 2019;159:572\u201381.","journal-title":"Procedia Comput Sci"},{"key":"353_CR11","doi-asserted-by":"crossref","unstructured":"Gasmi H, Laval J, Bouras A. Cold-start cybersecurity ontology population using information extraction with LSTM. In 2019 International Conference on Cyber Security for Emerging Technologies (CSET) IEEE. 2019:1\u20136.","DOI":"10.1109\/CSET.2019.8904905"},{"key":"353_CR12","doi-asserted-by":"crossref","unstructured":"Jayawardana V, Lakmal D, de Silva N, Perera AS, Sugathadasa K, Ayesha B, Perera M. Semi-supervised instance population of an ontology using word vector embedding. In: Proceedings of the International Conference on Advances in ICT for Emerging Regions (ICTer 2017) IEEE. 2017:1\u20137.","DOI":"10.1109\/ICTER.2017.8257822"},{"key":"353_CR13","unstructured":"Suchanek F, Ifrim G, Weikum G. LEILA: Learning to extract information by linguistic analysis. In Proceedings of the 2nd Workshop on Ontology Learning and Population: Bridging the Gap between Text and Knowledge ; 2006. p. 18-25."},{"key":"353_CR14","unstructured":"Grootendorst M. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203 05794. 2022."},{"key":"353_CR15","unstructured":"Plotkin SA, Orenstein WA, Offit PA, Edwards KM, editors. Plotkin\u2019s vaccines (7th ed.). 2018 Elsevier."},{"key":"353_CR16","unstructured":"Grootendorst M. KeyBERT: Minimal keyword extraction with BERT. 2020."},{"key":"353_CR17","unstructured":"Honnibal M, Montani I, Van Landeghem S, Boyd A. spaCy: Industrial-strength natural language processing in Python. 2023."},{"key":"353_CR18","doi-asserted-by":"crossref","unstructured":"Toutanova K, Klein D, Manning CD, Singer Y. Feature-rich part-of-speech tagging with a cyclic dependency network. In: Proceedings of NAACL-HLT Association for Computational Linguistics; Association for Computational Linguistics; 2003. p. 173-80.","DOI":"10.3115\/1073445.1073478"},{"key":"353_CR19","unstructured":"Santorini B. Part-of-speech tagging guidelines for the Penn Treebank Project. Technical Report MS-CIS-90-47. 1990."},{"issue":"29","key":"353_CR20","doi-asserted-by":"publisher","first-page":"861","DOI":"10.21105\/joss.00861","volume":"3","author":"L McInnes","year":"2018","unstructured":"McInnes L, Healy J, Saul N, Gro\u00dfberger L. UMAP: uniform manifold approximation and projection. J Open Source Softw. 2018;3(29):861.","journal-title":"J Open Source Softw"},{"key":"353_CR21","doi-asserted-by":"crossref","unstructured":"Campello RJGB, Moulavi D, Sander J. Hierarchical density estimates for data clustering, visualization, and outlier detection. ACM Trans Knowl Discov Data. 2015;10(1).","DOI":"10.1145\/2733381"},{"issue":"11","key":"353_CR22","doi-asserted-by":"publisher","first-page":"205","DOI":"10.21105\/joss.00205","volume":"2","author":"L McInnes","year":"2017","unstructured":"McInnes L, Healy J, Astels S. hdbscan: Hierarchical density-based clustering. J Open Source Softw. 2017;2(11):205.","journal-title":"J Open Source Softw"},{"key":"353_CR23","doi-asserted-by":"crossref","unstructured":"Lewis M, Liu Y, Goyal N, Ghazvininejad M, Mohamed A, Levy O, Stoyanov V, Zettlemoyer L. BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics Association for Computational Linguistics; 2020. p. 7871-80.","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"353_CR24","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s13326-021-00245-1","volume":"12","author":"S Babcock","year":"2021","unstructured":"Babcock S, Smith B, Cowell L, Shapiro JS, Hong C, Warner J, et al. The Infectious Disease Ontology in the age of COVID-19. J Biomedical Semant. 2021;12:15.","journal-title":"J Biomedical Semant"},{"key":"353_CR25","unstructured":"Ngo DH, Kemp M, Truran D, Koopman B, Metke-Jimenez A. Semantic search for large-scale clinical ontologies. AMIA Annu Symp Proc. 2021;2021:910-9."},{"key":"353_CR26","doi-asserted-by":"crossref","unstructured":"Chandra R, Shukla A, Tiwari S, Agarwal S, Svafrullah M, Adiyarta K. Natural language processing and ontology-based decision support system for diabetic patients. In: Proceedings of the 9th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI). IEEE; 2022. p. 13-18.","DOI":"10.23919\/EECSI56542.2022.9946601"},{"issue":"1","key":"353_CR27","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1186\/s13326-024-00318-x","volume":"15","author":"J Li","year":"2024","unstructured":"Li J, Li Y, Pan Y, Guo J, Sun Z, Li F, He Y, Tao C Mapping vaccine names in clinical trials to vaccine ontology using cascaded fine-tuned domain-specific language models. J Biomedical Semant. 2024;15(1):14.","journal-title":"J Biomedical Semant"},{"issue":"1","key":"353_CR28","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1186\/s12911-023-02409-8","volume":"24","author":"AM Simms","year":"2024","unstructured":"Simms AM, Kanakia A, Sipra M, Dutta B, Southall N. A patient safety knowledge graph supporting vaccine product development. BMC Med Inf Decis Mak. 2024;24(1):10.","journal-title":"BMC Med Inf Decis Mak"},{"issue":"1","key":"353_CR29","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1186\/s13326-025-00331-8","volume":"16","author":"Z Wang","year":"2025","unstructured":"Wang Z, Li X, Zheng J, He Y. Unveiling differential adverse event profiles in vaccines via LLM text embeddings and ontology semantic analysis. J Biomedical Semant. 2025;16(1):10.","journal-title":"J Biomedical Semant"},{"key":"353_CR30","doi-asserted-by":"publisher","first-page":"108571","DOI":"10.1016\/j.engappai.2024.108571","volume":"133","author":"Y Chasseray","year":"2024","unstructured":"Chasseray Y, Barthe-Delano\u00eb AM, Volkman J, N\u00e9gny S, Le Lann JM. A generic hybrid method combining rules and machine learning to automate domain-independent ontology population. Eng Appl Artif Intell. 2024;133:108571.","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"353_CR31","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1177\/15705838251334528","volume":"20","author":"S Ayad","year":"2025","unstructured":"Ayad S, Khelifa Chibout L. Ontology population with large language models (LLMs): A case study on asbestos ontology. Appl Ontology. 2025;20(1):89\u2013106.","journal-title":"Appl Ontology"},{"issue":"3","key":"353_CR32","doi-asserted-by":"publisher","first-page":"1067","DOI":"10.1007\/s11280-022-01029-y","volume":"25","author":"H Yin","year":"2022","unstructured":"Yin H, Song X, Yang S, Li J. Sentiment analysis and topic modeling for COVID-19 vaccine discussions. World Wide Web. 2022;25(3):1067\u201383.","journal-title":"World Wide Web"},{"issue":"3","key":"353_CR33","doi-asserted-by":"publisher","first-page":"41","DOI":"10.3390\/biotech11030041","volume":"11","author":"I Scarpino","year":"2022","unstructured":"Scarpino I, Zucco C, Vallelunga R, Luzza F, Cannataro M. Investigating topic modeling techniques to extract meaningful insights in Italian long COVID narration. BioTech. 2022;11(3):41.","journal-title":"BioTech"},{"issue":"11","key":"353_CR34","first-page":"e00243722","volume":"39","author":"RPD Silva","year":"2023","unstructured":"Silva RPD, Pollettini JT, Pazin Filho A. Unsupervised natural language processing in the identification of patients with suspected COVID-19 infection. Cadernos de sa\u00fade p\u00fablica. 2023;39(11):e00243722.","journal-title":"Cadernos de sa\u00fade p\u00fablica"},{"issue":"3","key":"353_CR35","doi-asserted-by":"publisher","first-page":"2281729","DOI":"10.1080\/21645515.2023.2281729","volume":"19","author":"MR Biswas","year":"2023","unstructured":"Biswas MR, Shah Z. Extracting factors associated with vaccination from Twitter data and mapping to behavioral models. Hum Vaccines Immunotherapeutics. 2023;19(3):2281729.","journal-title":"Hum Vaccines Immunotherapeutics"},{"issue":"5","key":"353_CR36","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/0306-4573(88)90021-0","volume":"24","author":"G Salton","year":"1988","unstructured":"Salton G, Buckley C. Term-weighting approaches in automatic text retrieval. Inf Process Manag. 1988;24(5):513\u201323.","journal-title":"Inf Process Manag"},{"key":"353_CR37","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, et al. Scikit-learn: Machine learning in Python. J Mach Learn Res. 2011;12:2825\u201330.","journal-title":"J Mach Learn Res"},{"key":"353_CR38","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.ins.2013.02.029","volume":"236","author":"F Ren","year":"2013","unstructured":"Ren F, Sohrab MG. Class-indexing based term weighting for automatic text classification. Inf Sci. 2013;236:109\u201325.","journal-title":"Inf Sci"}],"container-title":["Journal of Biomedical Semantics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13326-026-00353-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-026-00353-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-026-00353-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T11:31:46Z","timestamp":1790076706000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13326-026-00353-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,3]]},"references-count":38,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["353"],"URL":"https:\/\/doi.org\/10.1186\/s13326-026-00353-w","relation":{},"ISSN":["2041-1480"],"issn-type":[{"value":"2041-1480","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,3]]},"assertion":[{"value":"17 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 April 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"19"}}