{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:20:20Z","timestamp":1740169220194,"version":"3.37.3"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011789","name":"Department of Science and Technology of Jilin Province","doi-asserted-by":"publisher","award":["No.20190303133SF"],"award-info":[{"award-number":["No.20190303133SF"]}],"id":[{"id":"10.13039\/501100011789","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3040408","type":"journal-article","created":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T21:21:44Z","timestamp":1606339304000},"page":"214454-214468","source":"Crossref","is-referenced-by-count":1,"title":["SUDIR: An Approach of Sensing Urban Text Data From Internet Resources Based on Deep Learning"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0971-7422","authenticated-orcid":false,"given":"Chaoran","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenghao","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1161"},{"key":"ref38","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2016.0082"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1030"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1101"},{"key":"ref30","article-title":"Bidirectional LSTM-CRF models for sequence tagging","author":"huang","year":"2015","journal-title":"arXiv 1508 01991"},{"key":"ref37","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"arXiv 1810 04805"},{"key":"ref36","article-title":"Efficient estimation of word representations in vector space","author":"mikolov","year":"2013","journal-title":"arXiv 1301 3781 [cs]"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2909641"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty449"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-2039"},{"key":"ref27","article-title":"Empower sequence labeling with task-aware neural language model","author":"liu","year":"2017","journal-title":"arXiv 1709 04109"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1283"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.07.047"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2483669.2483678"},{"key":"ref20","first-page":"1","article-title":"Chinese NER using CRFs and logic for the fourth SIGHAN bakeoff","author":"yu","year":"2008","journal-title":"Proc Sixth SIGHAN Workshop Chin Lang Process"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10844-017-0458-3"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICSC.2010.74"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3038670"},{"key":"ref23","first-page":"1185","article-title":"Semi-Markov conditional random fields for information extraction","author":"sarawagi","year":"2005","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1144"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-50496-4_20"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2006.889970"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3115\/1690219.1690290"},{"journal-title":"Robust Tests for Equality of Variances in Contribution to Probability and Statistics","year":"1960","author":"levene","key":"ref59"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2023"},{"key":"ref57","article-title":"Word2vec parameter learning explained","author":"rong","year":"2014","journal-title":"arXiv 1411 2738"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/DSDE.2010.14"},{"key":"ref55","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"ester","year":"1996","journal-title":"Proc KDD"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/584792.584877"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2008.2006641"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2016.7498308"},{"key":"ref10","article-title":"Location name extraction from targeted text streams using gazetteer-based statistical language models","author":"al-olimat","year":"2017","journal-title":"arXiv 1708 03105"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.5311\/JOSIS.2014.9.170"},{"key":"ref40","article-title":"An efficient framework for learning sentence representations","author":"logeswaran","year":"2018","journal-title":"arXiv 1803 02893"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609582"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2684822.2685296"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2015.15"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IIAI-AAI.2015.203"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/304181.304187"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1162\/089120105775299177"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LAWEB.2005.38"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3202662","article-title":"Location extraction from social media: Geoparsing, location disambiguation, and geotagging","volume":"36","author":"middleton","year":"2018","journal-title":"ACM Trans Inf Syst"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"31","DOI":"10.9756\/BIJSESC.9018","article-title":"Hybridization approach to classify big data using social Internet of Things","volume":"9","author":"s","year":"2019","journal-title":"Bonfring International Journal of Software Engineering and Soft Computing"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2018.05.007"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/SMAP.2014.27"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2016.02.011"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1080\/13658816.2015.1133820","article-title":"Enabling maps\/location searches on mobile devices: Constructing a POI database via focused crawling and information extraction","volume":"30","author":"chuang","year":"2016","journal-title":"Int J Geographical Inf Sci"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.21236\/ADA470494"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-4007"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/988672.988700"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICWS.2017.37"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00802"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2005.19"},{"article-title":"Improving language understanding with unsupervised learning","year":"2018","author":"radford","key":"ref42"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-019-05794-2"},{"key":"ref43","article-title":"Pre-training with whole word masking for chinese BERT","author":"cui","year":"2019","journal-title":"arXiv 1906 08101"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09270026.pdf?arnumber=9270026","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T21:47:57Z","timestamp":1643147277000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9270026\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":59,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3040408","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2020]]}}}