{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T01:59:08Z","timestamp":1769911148478,"version":"3.49.0"},"reference-count":41,"publisher":"Elsevier BV","issue":"4","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602439"],"award-info":[{"award-number":["61602439"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61472400"],"award-info":[{"award-number":["61472400"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91746301"],"award-info":[{"award-number":["91746301"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing &amp; Management"],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1016\/j.ipm.2018.10.020","type":"journal-article","created":{"date-parts":[[2018,12,28]],"date-time":"2018-12-28T19:01:59Z","timestamp":1546023719000},"page":"1484-1493","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":9,"title":["Learning representations for quality estimation of crowdsourced submissions"],"prefix":"10.1016","volume":"56","author":[{"given":"Shanshan","family":"Lyu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wentao","family":"Ouyang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huawei","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueqi","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.ipm.2018.10.020_bib0001","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.ipm.2015.03.004","article-title":"Studying emotion induced by music through a crowdsourcing game","volume":"52","author":"Aljanaki","year":"2016","journal-title":"Information Processing and Management"},{"issue":"6","key":"10.1016\/j.ipm.2018.10.020_bib0002","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1016\/j.ipm.2012.01.004","article-title":"Using crowdsourcing for TREC relevance assessment","volume":"48","author":"Alonso","year":"2012","journal-title":"Information Processing and Management"},{"key":"10.1016\/j.ipm.2018.10.020_bib0003","series-title":"KDD","first-page":"554","article-title":"Statistical quality estimation for general crowdsourcing tasks","author":"Baba","year":"2013"},{"issue":"8","key":"10.1016\/j.ipm.2018.10.020_bib0004","doi-asserted-by":"crossref","first-page":"1798","DOI":"10.1109\/TPAMI.2013.50","article-title":"Representation learning: A review and new perspectives","volume":"35","author":"Bengio","year":"2013","journal-title":"IEEE TPAMI"},{"key":"10.1016\/j.ipm.2018.10.020_bib0005","series-title":"Pattern recognition and machine learning","author":"Bishop","year":"2006"},{"key":"10.1016\/j.ipm.2018.10.020_bib0006","series-title":"ICML","first-page":"89","article-title":"Learning to rank using gradient descent","author":"Burges","year":"2005"},{"key":"10.1016\/j.ipm.2018.10.020_bib0007","series-title":"ICML","first-page":"129","article-title":"Learning to rank: From pairwise approach to listwise approach","author":"Cao","year":"2007"},{"key":"10.1016\/j.ipm.2018.10.020_bib0008","doi-asserted-by":"crossref","first-page":"20","DOI":"10.2307\/2346806","article-title":"Maximum likelihood estimation of observer error-rates using the em algorithm","author":"Dawid","year":"1979","journal-title":"Applied Statistics"},{"key":"10.1016\/j.ipm.2018.10.020_bib0009","series-title":"WWW","first-page":"367","article-title":"Pick-a-crowd: Tell me what you like, and i\u2019ll tell you what to do","author":"Difallah","year":"2013"},{"issue":"6","key":"10.1016\/j.ipm.2018.10.020_bib0010","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1016\/j.ipm.2018.08.003","article-title":"Quality flaw prediction in spanish wikipedia: A case of study with verifiability flaws","volume":"54","author":"Ferretti","year":"2018","journal-title":"Information Processing and Management"},{"issue":"Nov","key":"10.1016\/j.ipm.2018.10.020_bib0011","first-page":"933","article-title":"An efficient boosting algorithm for combining preferences","volume":"4","author":"Freund","year":"2003","journal-title":"JMLR"},{"key":"10.1016\/j.ipm.2018.10.020_bib0012","series-title":"AAAI","first-page":"2000","article-title":"Learning invariant deep representation for nir-vis face recognition.","author":"He","year":"2017"},{"key":"10.1016\/j.ipm.2018.10.020_bib0013","series-title":"WWW","first-page":"143","article-title":"Quizz: Targeted crowdsourcing with a billion (potential) users","author":"Ipeirotis","year":"2014"},{"key":"10.1016\/j.ipm.2018.10.020_bib0014","unstructured":"Kingma, D., & Ba, J. (2014). Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980."},{"issue":"2","key":"10.1016\/j.ipm.2018.10.020_bib0015","first-page":"97","article-title":"Truth finding on the deep web: Is the problem solved?","volume":"6","author":"Li","year":"2012","journal-title":"PVLDB"},{"issue":"2","key":"10.1016\/j.ipm.2018.10.020_bib0016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2897350.2897352","article-title":"A survey on truth discovery","volume":"17","author":"Li","year":"2016","journal-title":"ACM SIGKDD Explorations Newsletter"},{"key":"10.1016\/j.ipm.2018.10.020_bib0017","series-title":"Learning to rank for information retrieval","author":"Liu","year":"2011"},{"key":"10.1016\/j.ipm.2018.10.020_bib0018","series-title":"Proceedings of the 2017 ACM on conference on information and knowledge management","first-page":"2183","article-title":"Truth discovery by claim and source embedding","author":"Lyu","year":"2017"},{"key":"10.1016\/j.ipm.2018.10.020_bib0019","series-title":"KDD","first-page":"745","article-title":"Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation","author":"Ma","year":"2015"},{"key":"10.1016\/j.ipm.2018.10.020_bib0020","series-title":"WWW","first-page":"843","article-title":"Using hierarchical skills for optimized task assignment in knowledge-intensive crowdsourcing","author":"Mavridis","year":"2016"},{"key":"10.1016\/j.ipm.2018.10.020_bib0021","series-title":"NIPS","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"Mikolov","year":"2013"},{"issue":"4","key":"10.1016\/j.ipm.2018.10.020_bib0022","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.ipm.2018.03.006","article-title":"Understanding crowdsourcing projects: A systematic review of tendencies, workflow, and quality management","volume":"54","author":"Neto","year":"2018","journal-title":"Information Processing and Management"},{"key":"10.1016\/j.ipm.2018.10.020_bib0023","series-title":"IPSN","first-page":"190","article-title":"Debiasing crowdsourced quantitative characteristics in local businesses and services","author":"Ouyang","year":"2015"},{"issue":"7","key":"10.1016\/j.ipm.2018.10.020_bib0024","first-page":"1621","article-title":"Aggregating crowdsourced quantitative claims: Additive and multiplicative models","volume":"28","author":"Ouyang","year":"2016","journal-title":"IEEE TKDE"},{"key":"10.1016\/j.ipm.2018.10.020_bib0025","series-title":"UBICOMP","first-page":"23","article-title":"If you see something, swipe towards it: Crowdsourced event localization using smartphones","author":"Ouyang","year":"2013"},{"key":"10.1016\/j.ipm.2018.10.020_bib0026","series-title":"WWW","first-page":"1009","article-title":"Latent credibility analysis","author":"Pasternack","year":"2013"},{"key":"10.1016\/j.ipm.2018.10.020_bib0027","series-title":"WWW","first-page":"1041","article-title":"Mining collective intelligence in diverse groups","author":"Qi","year":"2013"},{"key":"10.1016\/j.ipm.2018.10.020_bib0028","series-title":"CHI","first-page":"1403","article-title":"Human computation: a survey and taxonomy of a growing field","author":"Quinn","year":"2011"},{"key":"10.1016\/j.ipm.2018.10.020_bib0029","first-page":"1297","article-title":"Learning from crowds","volume":"99","author":"Raykar","year":"2010","journal-title":"JMLR"},{"key":"10.1016\/j.ipm.2018.10.020_bib0030","series-title":"WWW","first-page":"851","article-title":"Earthquake shakes twitter users: real-time event detection by social sensors","author":"Sakaki","year":"2010"},{"key":"10.1016\/j.ipm.2018.10.020_bib0031","series-title":"AAAI","first-page":"977","article-title":"Pairwise hits: Quality estimation from pairwise comparisons in creator-evaluator crowdsourcing process.","author":"Sunahase","year":"2017"},{"key":"10.1016\/j.ipm.2018.10.020_bib0032","series-title":"WWW","first-page":"155","article-title":"Community-based bayesian aggregation models for crowdsourcing","author":"Venanzi","year":"2014"},{"key":"10.1016\/j.ipm.2018.10.020_bib0033","series-title":"NIPS","first-page":"2424","article-title":"The multidimensional wisdom of crowds","author":"Welinder","year":"2010"},{"key":"10.1016\/j.ipm.2018.10.020_bib0034","series-title":"NIPS","first-page":"2035","article-title":"Whose vote should count more: Optimal integration of labels from labelers of unknown expertise","author":"Whitehill","year":"2009"},{"key":"10.1016\/j.ipm.2018.10.020_bib0035","series-title":"KDD","first-page":"1935","article-title":"Towards confidence in the truth: A bootstrapping based truth discovery approach","author":"Xiao","year":"2016"},{"key":"10.1016\/j.ipm.2018.10.020_bib0036","series-title":"SIGIR","first-page":"391","article-title":"Adarank: A boosting algorithm for information retrieval","author":"Xu","year":"2007"},{"issue":"6","key":"10.1016\/j.ipm.2018.10.020_bib0037","first-page":"796","article-title":"Truth discovery with multiple conflicting information providers on the web","volume":"20","author":"Yin","year":"2008","journal-title":"IEEE TKDE"},{"key":"10.1016\/j.ipm.2018.10.020_bib0038","series-title":"HLT","first-page":"1220","article-title":"Crowdsourcing translation: Professional quality from non-professionals","author":"Zaidan","year":"2011"},{"issue":"6","key":"10.1016\/j.ipm.2018.10.020_bib0039","first-page":"550","article-title":"A bayesian approach to discovering truth from conflicting sources for data integration","volume":"5","author":"Zhao","year":"2012","journal-title":"PVLDB"},{"key":"10.1016\/j.ipm.2018.10.020_bib0040","series-title":"AAAI","first-page":"3532","article-title":"Community-based question answering via asymmetric multi-faceted ranking network learning.","author":"Zhao","year":"2017"},{"key":"10.1016\/j.ipm.2018.10.020_bib0041","series-title":"KDD","first-page":"1593","article-title":"Debiasing crowdsourced batches","author":"Zhuang","year":"2015"}],"container-title":["Information Processing &amp; Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457318304965?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457318304965?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2019,8,8]],"date-time":"2019-08-08T01:40:04Z","timestamp":1565228404000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457318304965"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":41,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,7]]}},"alternative-id":["S0306457318304965"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2018.10.020","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2019,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Learning representations for quality estimation of crowdsourced submissions","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2018.10.020","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2018 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}]}}