{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T19:18:31Z","timestamp":1782933511840,"version":"3.54.5"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"EU MOnitoring Outbreak events for Disease surveillance in a data science context","award":["874850"],"award-info":[{"award-number":["874850"]}]},{"name":"\u201cAmbassade de France\u2014Nairobi,\u201d French General Directorate for Food"},{"DOI":"10.13039\/100005825","name":"National Research Institute for Agriculture, Food and the Environment (INRAE), French Agricultural Research Centre for International Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2026.3666022","type":"journal-article","created":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T20:48:59Z","timestamp":1771879739000},"page":"29566-29589","source":"Crossref","is-referenced-by-count":1,"title":["Novelty Detection in Event Surveillance Documents"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7408-1710","authenticated-orcid":false,"given":"Edmond","family":"Menya","sequence":"first","affiliation":[{"name":"Université de Montpellier, Montpellier, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0536-6277","authenticated-orcid":false,"given":"Roberto","family":"Interdonato","sequence":"additional","affiliation":[{"name":"CIRAD, Montpellier, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0968-5742","authenticated-orcid":false,"given":"Dickson","family":"Owuor","sequence":"additional","affiliation":[{"name":"SCES, Strathmore University, Nairobi, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3272-8568","authenticated-orcid":false,"given":"Mathieu","family":"Roche","sequence":"additional","affiliation":[{"name":"CIRAD, Montpellier, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"3741","article-title":"Enriching epidemiological thematic features for disease surveillance corpora classification","volume-title":"Proc. Lang. Resour. Eval. Conf.","author":"Menya"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.onehlt.2021.100357"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0050151"},{"key":"ref4","volume-title":"Report of the WHO\/FAO\/OIE Joint Consultation on Emerging Zoonotic Diseases\/in Collaboration With the Health Council of The Netherlands","year":"2004"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2019.105163"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1086\/422003"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3115\/1220575.1220589"},{"key":"ref8","first-page":"2802","article-title":"Novelty goes Deep. A deep neural solution to document level novelty detection","volume-title":"Proc. 27th Int. Conf. Comput. Linguistics","author":"Ghosal"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1017\/S1351324920000194"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-70239-6_30"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2015.06.005"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-78105-1_39"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123894"},{"key":"ref14","volume-title":"Early Detection, Assessment and Response To Acute Public Health Events: Implementation of Early Warning and Response With a Focus on Event-based Surveillance: Interim Version","year":"2014"},{"key":"ref15","volume-title":"A Guide To Establishing Event-based Surveillance","year":"2008"},{"key":"ref16","article-title":"Spotting rumors via novelty detection","author":"Qin","year":"2016","journal-title":"arXiv:1611.06322"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2021.102740"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCNT49239.2020.9225588"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1162\/coli_a_00429"},{"issue":"140","key":"ref20","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2019","journal-title":"J. Mach. Learn. Res."},{"key":"ref21","volume-title":"GPT-4 Technical Report","year":"2024"},{"key":"ref22","article-title":"DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning","author":"Guo","year":"2025","journal-title":"arXiv:2501.12948"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1002\/asi.23228"},{"key":"ref24","first-page":"2802","article-title":"TAP-DLND 1.0: A corpus for document level novelty detection","volume-title":"Proc. 11th Int. Conf. Lang. Resour. Eval. (LREC)","author":"Ghosal"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0254034"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/1506250.1506256"},{"key":"ref27","article-title":"The seventh Pascal recognizing textual entailment challenge","author":"Bentivogli","year":"2008"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1504\/IJKEDM.2011.037645"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/WI-IAT.2012.128"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/11562382_54"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/11736790_9"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3115\/1654536.1654538"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00397"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-41230-1_5"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"issue":"6","key":"ref36","first-page":"198","article-title":"Text anomaly detection advancements, challenges and pathways: A systematic literature review","volume":"11","author":"-Sulyman","year":"2025","journal-title":"J. Logistics, Inform. Service Sci."},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.findings-emnlp.133"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.472"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1264"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2124"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-5446"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-5819"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2020.106356"},{"issue":"1","key":"ref44","first-page":"33","article-title":"Text tiling: Segmenting text into multi-paragraph subtopic passages","volume":"23","author":"Hearst","year":"1997","journal-title":"Comput. Linguistics"},{"key":"ref45","volume-title":"Natural Language Processing With Python: Analyzing Text With the Natural Language Toolkit","author":"Bird","year":"2009"},{"key":"ref46","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arxiv: 1810.04805"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz682"},{"key":"ref48","volume-title":"PADI-Web corpus: News manually labeled","author":"Rabatel","year":"2017"},{"key":"ref49","volume-title":"PADI-Web corpus used for the EpidBioELECTRA approach","author":"Menya","year":"2023"},{"key":"ref50","first-page":"1","article-title":"Gdelt: Global data on events, location, and tone, 1979\u20132012","volume":"2","author":"Kalev Leetaru","year":"1979","journal-title":"ISA Annu. Conv."},{"key":"ref51","volume-title":"Famine Early Warning Systems Network","year":"2018"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1057\/s41599-023-01559-4"},{"key":"ref53","first-page":"1","article-title":"Superglue: A stickier benchmark for general-purpose language understanding systems","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref54","first-page":"1","article-title":"Beyond the imitation game: Quantifying and extrapolating the capabilities of language models","volume-title":"Proc. Trans. Mach. Learn. Res.","author":"Srivastava"},{"key":"ref55","article-title":"Parameter-efficient fine-tuning for large models: A comprehensive survey","author":"Han","year":"2024","journal-title":"arXiv:2403.14608"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1907.11692"},{"key":"ref57","article-title":"Deberta: Decoding-enhanced BERT with disentangled attention","author":"He","year":"2021","journal-title":"arXiv:2006.03654"},{"key":"ref58","first-page":"1","article-title":"Language models are few-shot learners","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Brown"},{"key":"ref59","first-page":"26","article-title":"Advances in domain independent linear text segmentation","volume-title":"Proc. 1st North Amer. Chapter Assoc. Comput. Linguistics","author":"Choi"},{"key":"ref60","first-page":"9486","article-title":"Unsupervised text segmentation using contextualized sentence embeddings","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Glava\u0161"},{"key":"ref61","first-page":"553","article-title":"How text segmentation algorithms gain from topic models","volume-title":"Proc. Conf. North American Chapter Assoc. Comput. Linguistics, Human Lang. Technol.","author":"Riedl"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S16-2016"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-73848-2_3"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1266"},{"key":"ref65","article-title":"Deep-significance-easy and meaningful statistical significance testing in the age of neural networks","author":"Ulmer","year":"2022","journal-title":"arXiv:2204.06815"},{"key":"ref66","article-title":"Large language models are human-level prompt engineers","author":"Zhou","year":"2023","journal-title":"arXiv:2211.01910"},{"key":"ref67","article-title":"LoRa: Low-rank adaptation of large language models","author":"Hu","year":"2021","journal-title":"arXiv:2106.09685"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11407933.pdf?arnumber=11407933","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T20:57:22Z","timestamp":1772485042000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11407933\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":67,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3666022","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}