{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:18:28Z","timestamp":1740169108875,"version":"3.37.3"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2018]]},"DOI":"10.1109\/access.2018.2871168","type":"journal-article","created":{"date-parts":[[2018,9,19]],"date-time":"2018-09-19T19:23:33Z","timestamp":1537385013000},"page":"54900-54909","source":"Crossref","is-referenced-by-count":1,"title":["Learning Distance Metrics for Entity Resolution"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8898-5817","authenticated-orcid":false,"given":"Lingli","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5332-5242","authenticated-orcid":false,"given":"Xiaodan","family":"Shang","sequence":"additional","affiliation":[]},{"given":"Jinbao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jin","family":"Hu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.14778\/1920841.1920904"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1145\/3068335"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1109\/ACCESS.2017.2745708"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1109\/ACCESS.2018.2810267"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1109\/TKDE.2014.2320713"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1145\/3035918.3035960"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1145\/3035918.3035931"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/ICDE.2017.151"},{"key":"ref13","first-page":"267","article-title":"The field matching problem: Algorithms and applications","author":"monge","year":"1996","journal-title":"Proc Int'l Conf Knowledge Discovery and Data Mining"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1145\/146370.146380"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1145\/375360.375365"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1080\/01621459.1989.10478785"},{"year":"1991","author":"winkler","article-title":"An application of the Fellegi-Sunter model of record linkage to the 1990 U.S. Decennial Census","key":"ref17"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/TCYB.2016.2521767"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1016\/j.patcog.2016.11.010"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1126\/science.130.3381.954","article-title":"Automatic linkage of vital records","volume":"130","author":"newcombe","year":"1959","journal-title":"Science"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1109\/TNNLS.2017.2673241"},{"key":"ref3","first-page":"13","article-title":"A survey of text similarity approaches","volume":"68","author":"gomaa","year":"2013","journal-title":"Int J Comput Appl"},{"key":"ref27","article-title":"Deep features learning for medical image analysis with convolutional autoencoder neural network","author":"chen","year":"0","journal-title":"IEEE Trans Big Data"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1145\/1142473.1142599"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/TKDE.2007.250581"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/ACCESS.2017.2788700"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.14778\/3137765.3137833"},{"key":"ref7","first-page":"593","article-title":"Linking temporal records for profiling entities","author":"li","year":"2015","journal-title":"Proc ACM Int Conf Manage Data"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1109\/ICDE.2005.125"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1145\/956750.956759"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1145\/2983323.2983831"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/ACCESS.2017.2669203"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1109\/ACCESS.2017.2694446"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1109\/ACCESS.2017.2756102"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.ijar.2017.01.003","article-title":"ERBlox: Combining matching dependencies with machine learning for entity resolution","volume":"83","author":"zeinab","year":"2017","journal-title":"Int J Approx Reasoning"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1080\/01621459.2015.1105807"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.1109\/JSTARS.2017.2657600"},{"key":"ref25","first-page":"1379","article-title":"Active learning for large-scale entity resolution","author":"kun","year":"2017","journal-title":"Proc CIKM"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8274985\/08468162.pdf?arnumber=8468162","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T17:36:37Z","timestamp":1643218597000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8468162\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/access.2018.2871168","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2018]]}}}