{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T21:01:49Z","timestamp":1770498109691,"version":"3.49.0"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education","award":["5120200913674"],"award-info":[{"award-number":["5120200913674"]}]},{"name":"Ministry of Education"},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3339774","type":"journal-article","created":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T19:40:53Z","timestamp":1701978053000},"page":"139521-139533","source":"Crossref","is-referenced-by-count":5,"title":["Extracting Fallen Objects on the Road From Accident Reports Using a Natural Language Processing Model-Based Approach"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2484-8458","authenticated-orcid":false,"given":"Seung-Seok","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, Chonnam National University, Gwangju, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0066-8054","authenticated-orcid":false,"given":"So-Mi","family":"Cha","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Chonnam National University, Gwangju, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1544-6377","authenticated-orcid":false,"given":"Bonggyun","family":"Ko","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Chonnam National University, Gwangju, South Korea"}]},{"given":"Je Jin","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Chonnam National University, Gwangju, South Korea"}]}],"member":"263","reference":[{"issue":"7","key":"ref1","first-page":"1","article-title":"The prevalence of motor vehicle crashes involving road debris, United States, 2011\u20132014","volume":"20","author":"Tefft","year":"2016","journal-title":"Age"},{"key":"ref2","volume-title":"Highway to Help: Secure your Load Makes Roads Safer With the Steadfast Support of Its Partners in Safety","year":"2019"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.amar.2016.04.001"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-017-0418-4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2018.03.011"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2015.09.005"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2007.62"},{"issue":"2","key":"ref8","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1109\/TITS.2013.2291241","article-title":"Web-based traffic sentiment analysis: Methods and applications","volume":"15","author":"Cao","year":"2014","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2014.6957803"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-85729-320-6_7"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P14-1119"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3115\/1119282.1119287"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1147\/rd.14.0309"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-4571(199504)46:3<162::AID-ASI2>3.0.CO;2-6"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1002\/asi.4630260106"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1142\/S0218213004001466"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3115\/1119355.1119383"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-77094-7_41"},{"issue":"4","key":"ref19","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1023\/A:1009976227802","article-title":"Learning algorithms for keyphrase extraction","volume":"2","author":"Turney","year":"2000","journal-title":"Inf. Retr."},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3115\/1698239.1698242"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1150"},{"key":"ref22","first-page":"1608","article-title":"Automatic hypertext keyphrase detection","volume-title":"Proc. IJCAI","volume":"5","author":"Kelleher"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/1135777.1135813"},{"key":"ref24","article-title":"Coherent keyphrase extraction via web mining","author":"Turney","year":"2003","journal-title":"arXiv:cs\/0308033"},{"key":"ref25","article-title":"Learning to extract keyphrases from text","author":"Turney","year":"2002","journal-title":"arXiv:cs\/0212013"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44686-9_47"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/11775300_8"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1572113"},{"key":"ref29","first-page":"4","article-title":"HUMB: Automatic key term extraction from scientific articles in Grobid","volume-title":"Proc. SemEval Workshop","author":"Lopez"},{"key":"ref30","first-page":"282","article-title":"Conditional random fields: Probabilistic models for segmenting and labeling sequence data","volume-title":"Proc. 18th Int. Conf. Mach. Learn. (ICML)","author":"Lafferty"},{"issue":"3","key":"ref31","first-page":"1169","article-title":"Automatic keyword extraction from documents using conditional random fields","volume":"4","author":"Zhang","year":"2008","journal-title":"J. Comput. Inf. Syst."},{"key":"ref32","article-title":"Keyphrase extraction using sequential labeling","author":"Gollapalli","year":"2016","journal-title":"arXiv:1608.00329"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313642"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref35","volume-title":"Improving language understanding by generative pre-training","author":"Radford","year":"2018"},{"key":"ref36","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv:1810.04805"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref38","article-title":"ELECTRA: Pre-training text encoders as discriminators rather than generators","author":"Clark","year":"2020","journal-title":"arXiv:2003.10555"},{"key":"ref39","volume-title":"KoBERT: Korean BERT Pre-Trained Cased","year":"2019"},{"key":"ref40","volume-title":"Koelectra: Pretrained Electra Model for Korean","year":"2020"},{"key":"ref41","first-page":"591","article-title":"Maximum entropy Markov models for information extraction and segmentation","volume-title":"Proc. ICML","volume":"17","author":"McCallum"},{"key":"ref42","volume-title":"Data Mining: Concepts and Techniques","author":"Han","year":"2012"},{"key":"ref43","first-page":"249","article-title":"Performance measures for information extraction","volume-title":"Proc. DARPA Broadcast News Workshop","author":"Makhoul"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3115\/1072399.1072403"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10348520.pdf?arnumber=10348520","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T02:34:16Z","timestamp":1705026856000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10348520\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3339774","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}