{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:22:09Z","timestamp":1768782129086,"version":"3.49.0"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T00:00:00Z","timestamp":1641772800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T00:00:00Z","timestamp":1641772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41871305"],"award-info":[{"award-number":["41871305"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2017YFC0602204"],"award-info":[{"award-number":["2017YFC0602204"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences","award":["CUGQY1945"],"award-info":[{"award-number":["CUGQY1945"]}]},{"name":"Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education; the Fundamental Research Funds for the Central Universities","award":["GLAB2019ZR02"],"award-info":[{"award-number":["GLAB2019ZR02"]}]},{"name":"Major scientific and technological innovation projects in Shandong Province","award":["2019JZZY020105"],"award-info":[{"award-number":["2019JZZY020105"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Earth Sci Inform"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s12145-021-00756-6","type":"journal-article","created":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T10:02:59Z","timestamp":1641808979000},"page":"573-584","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Extraction of temporal information from social media messages using the BERT model"],"prefix":"10.1007","volume":"15","author":[{"given":"Kai","family":"Ma","sequence":"first","affiliation":[]},{"given":"Yongjian","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Miao","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Xuejing","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Qinjun","family":"Qiu","sequence":"additional","affiliation":[]},{"given":"Sanfeng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,10]]},"reference":[{"key":"756_CR1","unstructured":"Ahn D, Adafre F, De Rijke M (2005) Towards task-based temporal extraction and recognition. In: Dagstuhl Seminar Proceedings. Schloss Dagstuhl-Leibniz-Zentrum f\u00fcr Informatik"},{"key":"756_CR2","doi-asserted-by":"publisher","unstructured":"Alfattni G, Peek N, Nenadic G (2020) Extraction of temporal relations from clinical free text: a systematic review of current approaches. J Biomed Inform 108:103488. https:\/\/doi.org\/10.1016\/j.jbi.2020.103488","DOI":"10.1016\/j.jbi.2020.103488"},{"key":"756_CR3","unstructured":"Amig\u00f3 E, Artiles J, Li Q, Ji H (2021) An evaluation framework for aggregated temporal information extraction.\u00a0In: SIGIR-2011 workshop on entity-oriented search"},{"issue":"6","key":"756_CR4","doi-asserted-by":"publisher","first-page":"S54","DOI":"10.1016\/j.jbi.2013.09.007","volume":"46","author":"Y-C Chang","year":"2013","unstructured":"Chang Y-C, Dai H-J, Wu JC-Y, Chen J-M, Tsai RT-H, Hsu W-L(2013) TEMPTING system: A hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries. J Biomed Inform 46(6):S54\u2013S62","journal-title":"J Biomed Inform"},{"key":"756_CR5","doi-asserted-by":"publisher","first-page":"104130","DOI":"10.1016\/j.engappai.2020.104130","volume":"99","author":"SS Deepika","year":"2021","unstructured":"Deepika SS, Tv G (2021)Pattern-based bootstrapping framework for biomedical relation extraction. Eng Appl Artif Intell 99:104130. https:\/\/doi.org\/10.1016\/j.engappai.2020.104130","journal-title":"Eng Appl Artif Intell"},{"key":"756_CR6","unstructured":"Devlin J, Chang M, Lee K et al (2019) Bert: pre-training of deep bidirectional transformers for language understanding [C]. Proc of Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. ACL, Stroudsburg, 4171-4186"},{"issue":"2","key":"756_CR7","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1207\/s15516709cog1402_1","volume":"14","author":"JL Elman","year":"1990","unstructured":"Elman JL (1990) Finding structure in time. Cogn Sci 14(2):179\u2013211","journal-title":"Cogn Sci"},{"key":"756_CR8","unstructured":"Ferro L, Gerberl, Mani I et al. Tides 2005 standard for the annotation of temporal expressions [EB \/OL]. (2005-09-10) [2019-05-27]. http:\/\/www.timex2.mitre.org"},{"key":"756_CR9","doi-asserted-by":"crossref","unstructured":"Ghahabi O, Hernando J (2018) Restricted boltzmann machines for vector representation of speech in speaker recognition. Comput Speech Lang 47:16\u201329","DOI":"10.1016\/j.csl.2017.06.007"},{"key":"756_CR10","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1017\/S1351324919000044","volume":"25","author":"C Giannella","year":"2019","unstructured":"Giannella C, Winder R, Jubinski J (2019) Annotation projection for temporal information extraction. Nat Lang Eng 25:385\u2013403. https:\/\/doi.org\/10.1017\/S1351324919000044","journal-title":"Nat Lang Eng"},{"issue":"4","key":"756_CR11","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1007\/s12145-020-00485-2","volume":"13","author":"K Jayapriya","year":"2020","unstructured":"Jayapriya K, Jacob IJ, Darney PE (2020) Hyperspectral image classification using multi-task feature leverage with multi-variant deep learning. Earth Sci Inf 13(4):1093\u20131102","journal-title":"Earth Sci Inf"},{"key":"756_CR12","doi-asserted-by":"crossref","unstructured":"Jeong YS, Kim ZM, Do HW, Lim CG, Choi HJ (2015) Temporal information extraction from Korean texts. In Proceedings of the Nineteenth Conference on Computational Natural Language Learning, pp 279-288","DOI":"10.18653\/v1\/K15-1028"},{"key":"756_CR13","unstructured":"Kolomiyets O, Moens M-F(2010) KUL: Recognition and normalization of temporal expressions. SemEval@ACL, 325\u2013328"},{"key":"756_CR14","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.jbi.2017.07.012","volume":"73","author":"K Kreimeyer","year":"2017","unstructured":"Kreimeyer K, Foster M, Pandey A, Arya N, Halford G, Jones SF, Forshee R, Walderhaug M, Botsis T (2017) Natural language processing systems for capturing and standardizing unstructured clinical information: a systematic review. J Biomed Inform 73:14\u201329","journal-title":"J Biomed Inform"},{"key":"756_CR15","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1613\/jair.1.11727","volume":"66","author":"A Leeuwenberg","year":"2019","unstructured":"Leeuwenberg A, Moens M-F(2019) A survey on temporal reasoning for temporal information extraction from text. J Artif Intell Res 66:341\u2013380. https:\/\/doi.org\/10.1613\/jair.1.11727","journal-title":"J Artif Intell Res"},{"key":"756_CR16","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1002\/asi.1126.abs","volume":"52","author":"W Li","year":"2001","unstructured":"Li W, Wong K-F, Yuan C (2001) Toward automatic Chinese temporal information extraction. JASIST 52:748\u2013762. https:\/\/doi.org\/10.1002\/asi.1126.abs","journal-title":"JASIST"},{"issue":"S3","key":"756_CR17","first-page":"191","volume":"39","author":"J Li","year":"2012","unstructured":"Li J, Tan H, Wang F (2012) Recognition of temporal expressions and their types in Chinese [J]. Comput Sci 39(S3):191\u2013194211","journal-title":"Comput Sci"},{"key":"756_CR18","doi-asserted-by":"publisher","unstructured":"Li Z, Li C, Long Yu, Wang X (2020) A system for automatically extracting clinical events with temporal information. BMC Med Inform Decis Mak 20. https:\/\/doi.org\/10.1186\/s12911-020-01208-9","DOI":"10.1186\/s12911-020-01208-9"},{"key":"756_CR19","doi-asserted-by":"publisher","unstructured":"Lin Y-K, Chen Hsiu-chin, Brown R (2013) MedTime: A temporal information extraction system for clinical narratives. J Biomed Inform 46. https:\/\/doi.org\/10.1016\/j.jbi.2013.07.012","DOI":"10.1016\/j.jbi.2013.07.012"},{"key":"756_CR20","doi-asserted-by":"publisher","unstructured":"Liu K, El-Gohary N (2017)Ontology-based semi-supervised conditional random fields for automated information extraction from bridge inspection reports. Autom Constr 81. https:\/\/doi.org\/10.1016\/j.autcon.2017.02.003","DOI":"10.1016\/j.autcon.2017.02.003"},{"key":"756_CR21","doi-asserted-by":"crossref","unstructured":"Ma K, Tian M, Tan Y, Xie X, Qiu Q (2021) What is this article about? Generative summarization with the BERT model in the geosciences domain. Earth Science Informatics. 1-16","DOI":"10.1007\/s12145-021-00695-2"},{"key":"756_CR22","doi-asserted-by":"crossref","unstructured":"Mani I,\u00a0Wilson G (2000) Robust temporal processing of news [C]. Proceedings of the 38th Annual Meeting on ACL, Hongkong, 69-76","DOI":"10.3115\/1075218.1075228"},{"key":"756_CR23","unstructured":"Martins B, Manguinhas H, Borbinha J, Siabato W (2021) A geo-temporal information extraction service for processing descriptive metadata in digital libraries"},{"key":"756_CR24","doi-asserted-by":"crossref","unstructured":"Meng Y, Rumshisky A, Romanov A (2017) Temporal information extraction for question answering using syntactic dependencies in an LSTM-based architecture.\u00a0arXiv preprint arXiv:1703.05851.","DOI":"10.18653\/v1\/D17-1092"},{"key":"756_CR25","doi-asserted-by":"publisher","unstructured":"Moharasan G, Ho T-B(2019) Extraction of temporal information from clinical narratives. J Healthc Inform Res 3. https:\/\/doi.org\/10.1007\/s41666-019-00049-0","DOI":"10.1007\/s41666-019-00049-0"},{"key":"756_CR26","unstructured":"Paramita P, Minard A-LM(2014) Fbk-hlt-time: a complete italian temporal processing system for eventi-evalita 2014. In: Fourth International Workshop EVALITA 2014, pp 44\u201349"},{"key":"756_CR27","doi-asserted-by":"crossref","unstructured":"Peters ME, Neumann M, Iyyer M et al (2018) Deep contextualized word representations [C]. Proc of Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. ACL, Stroudsburg, 2227-2237","DOI":"10.18653\/v1\/N18-1202"},{"issue":"4","key":"756_CR28","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1007\/s12145-019-00390-3","volume":"12","author":"Q Qiu","year":"2019","unstructured":"Qiu Q, Xie Z, Wu L et al (2019)BiLSTM-CRF for geological named entity recognition from the geoscience literature[J]. Earth Sci Inf 12(4):565\u2013579","journal-title":"Earth Sci Inf"},{"issue":"4","key":"756_CR29","doi-asserted-by":"publisher","first-page":"1393","DOI":"10.1007\/s12145-020-00527-9","volume":"13","author":"Q Qiu","year":"2020","unstructured":"Qiu Q, Xie Z, Wu L et al (2020) Automatic spatiotemporal and semantic information extraction from unstructured geoscience reports using text mining techniques[J]. Earth Sci Inf 13(4):1393\u20131410","journal-title":"Earth Sci Inf"},{"key":"756_CR30","doi-asserted-by":"publisher","unstructured":"Qu J, Ouyang D, Hua W, Ye, Yuxin, Li X (2018) Distant supervision for neural relation extraction integrated with word attention and property features. Neural Netw 100. https:\/\/doi.org\/10.1016\/j.neunet.2018.01.006","DOI":"10.1016\/j.neunet.2018.01.006"},{"key":"756_CR31","unstructured":"Radford A, Narasimhan K, Salimans T (2018) Improving language understanding with unsupervised learning [EB \/OL]. [2019-10-30]. https:\/\/www.openai.com\/blog\/language-unsupervised"},{"key":"756_CR32","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"D Rumelhart","year":"1986","unstructured":"Rumelhart D, Hinton G, Williams R (1986) Learning representations by back-propagating errors. Nature 323:533\u2013536","journal-title":"Nature"},{"key":"756_CR33","doi-asserted-by":"crossref","unstructured":"Sagcan M, Karagoz P (2015) Toponym recognition in social media for estimating the location of events. ICDM Workshops, 33\u201339","DOI":"10.1109\/ICDMW.2015.167"},{"issue":"3","key":"756_CR34","first-page":"1","volume":"32","author":"R Santos","year":"2017","unstructured":"Santos R, Murrietaflores P, Calado P, Martins B (2017) Toponym matching through deep neural networks. Int J Geogr Inf Sci 32(3):1\u201325","journal-title":"Int J Geogr Inf Sci"},{"issue":"05","key":"756_CR35","first-page":"538","volume":"36","author":"G Song","year":"2019","unstructured":"Song G, Zhang S, Jia F, Jiang S (2019) Temporal information extraction and normalization method in Chinese Texts [J]. J Geomat Sci Technol 36(05):538\u2013544","journal-title":"J Geomat Sci Technol"},{"key":"756_CR36","unstructured":"Str\u00f6tgen J, Gertz M (2010) Heideltime: High quality rule-based extraction and normalization of temporal expressions. In: Proceedings of the 5th International Workshop on Semantic Evaluation, pp 321-324"},{"key":"756_CR37","doi-asserted-by":"publisher","unstructured":"Tourille J, Ferret O, N\u00e9v\u00e9ol A, Tannier X (2017) Temporal information extraction from clinical text, 739-745. https:\/\/doi.org\/10.18653\/v1\/E17-2117","DOI":"10.18653\/v1\/E17-2117"},{"key":"756_CR38","unstructured":"Tourille J, Ferret O, Neveol A, Tannier X (2016) Extraction de relations temporelles dans des dossiers \u00e9lectroniques patient, in: Actes de la Conference Traitement Automatique des Langues Naturelles (TALN 2016, article court), Paris, France"},{"key":"756_CR39","first-page":"5998","volume-title":"Information Processing Systems 30","author":"A Vaswani","year":"2017","unstructured":"Vaswani A, Shazeer N, Parmar N et al (2017) Attention is all you need [C]. Advances in Neural. Information Processing Systems 30. Curran Associates, New York, pp 5998\u20136008"},{"key":"756_CR40","unstructured":"Verhagen M, Saur R, Caselli T, et al (2010)SemEval-2010 task 13: TempEval-2 [C]. Proceedings of the 5th International Workshop on Semantic Evaluation. Uppsala, Sweden, 57-62"},{"key":"756_CR41","doi-asserted-by":"publisher","unstructured":"Viani N, Kam J, Yin L, Bittar A, Dutta R, Patel R, Stewart R, Sumithra V (2020) Temporal information extraction from mental health records to identify duration of untreated psychosis. J Biomed Semantics 11. https:\/\/doi.org\/10.1186\/s13326-020-00220-2","DOI":"10.1186\/s13326-020-00220-2"},{"key":"756_CR42","doi-asserted-by":"crossref","unstructured":"Vicente-D\u00edez MT, Mart\u00ednez P (2009) Temporal semantics extraction for improving web search. DEXA Workshops, 69\u201373","DOI":"10.1109\/DEXA.2009.57"},{"key":"756_CR43","doi-asserted-by":"publisher","unstructured":"Wang W, Kreimeyer K, Woo E, Ball R, Foster M, Pandey A, Scott J, Botsis T (2016) A new algorithmic approach for the extraction of temporal associations from clinical narratives with an application to medical product safety surveillance reports. J Biomed Inform 62. https:\/\/doi.org\/10.1016\/j.jbi.2016.06.006","DOI":"10.1016\/j.jbi.2016.06.006"},{"issue":"3","key":"756_CR44","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1111\/tgis.12627","volume":"24","author":"J Wang","year":"2020","unstructured":"Wang J, Hu Y, Joseph K (2020) NeuroTPR: A neuro-net toponym recognition model for extracting locations from social media messages[J]. Trans GIS 24(3):719\u2013735","journal-title":"Trans GIS"},{"issue":"4","key":"756_CR45","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1016\/0893-6080(88)90007-X","volume":"1","author":"PJ Werbos","year":"1988","unstructured":"Werbos PJ (1988) Generalization of backpropagation with application to a recurrent gas market model. Neural Netw 1(4):339\u2013356","journal-title":"Neural Netw"},{"key":"756_CR46","doi-asserted-by":"publisher","unstructured":"Wong K-F, Xia Y, Li W, Yuan C (2012) An overview of temporal information extraction. Int J Comput Process Lang 18. https:\/\/doi.org\/10.1142\/S0219427905001225","DOI":"10.1142\/S0219427905001225"},{"issue":"04","key":"756_CR47","first-page":"3","volume":"24","author":"T Wu","year":"2010","unstructured":"Wu T, Zhou Y, Huang X, Wu L (2010) Chinese time expression recognition based on automatically generated. Basic Time Unit Rules 24(04):3\u201310","journal-title":"Basic Time Unit Rules"},{"key":"756_CR48","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1016\/j.engappai.2017.06.024","volume":"64","author":"L Yao","year":"2017","unstructured":"Yao L, Zhang Y, Chen Q, Qian H, Hu Z (2017) Mining coherent topics in documents using word embeddings and large-scale text data. Eng Appl Artif Intell 64:432\u2013439","journal-title":"Eng Appl Artif Intell"},{"issue":"06","key":"756_CR49","first-page":"1","volume":"30","author":"Z Zhang Chunju","year":"2014","unstructured":"Zhang Chunju Z, Xueying L, Ming W (2014) Temporal information analysis method in Chinese text [J]. Geogr Geo-Inf Sci 30(06):1\u20137","journal-title":"Geogr Geo-Inf Sci"},{"key":"756_CR50","doi-asserted-by":"publisher","unstructured":"Zhou X, Li H, Lu X, Duan H (2011) Temporal expression recognition and temporal relationship extraction from chinese narrative medical records. 2011 5th International Conference on Bioinformatics and Biomedical Engineering, Wuhan, pp 1-4. https:\/\/doi.org\/10.1109\/icbbe.2011.5780699","DOI":"10.1109\/icbbe.2011.5780699"},{"key":"756_CR51","doi-asserted-by":"publisher","unstructured":"Zhou P, Xu J, Qi Z, Bao H, Chen Z, Xu B (2018) Distant supervision for relation extraction with hierarchical selective attention. Neural Netw 108. https:\/\/doi.org\/10.1016\/j.neunet.2018.08.016","DOI":"10.1016\/j.neunet.2018.08.016"},{"key":"756_CR52","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1007\/s12145-020-00470-9","volume":"13","author":"X Zhou","year":"2020","unstructured":"Zhou X, Tong W, Li L (2020) Deep learning spatiotemporal air pollution data in China using data fusion. Earth Sci Inform 13:859\u2013868. https:\/\/doi.org\/10.1007\/s12145-020-00470-9","journal-title":"Earth Sci Inform"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00756-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-021-00756-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00756-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,10]],"date-time":"2022-02-10T02:20:40Z","timestamp":1644459640000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-021-00756-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,10]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["756"],"URL":"https:\/\/doi.org\/10.1007\/s12145-021-00756-6","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"value":"1865-0473","type":"print"},{"value":"1865-0481","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,10]]},"assertion":[{"value":"27 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}