{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T18:14:09Z","timestamp":1791224049264,"version":"4.1.0"},"reference-count":15,"publisher":"Association for Computing Machinery (ACM)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2012,2]]},"abstract":"<jats:p>\n            In practical data integration systems, it is common for the data sources being integrated to provide conflicting information about the same entity. Consequently, a major challenge for data integration is to derive the most complete and accurate integrated records from diverse and sometimes conflicting sources. We term this challenge the\n            <jats:italic>truth finding problem<\/jats:italic>\n            . We observe that some sources are generally more reliable than others, and therefore a good model of source quality is the key to solving the truth finding problem. In this work, we propose a probabilistic graphical model that can automatically infer true records and source quality without any supervision. In contrast to previous methods, our principled approach leverages a generative process of two types of errors (false positive and false negative) by modeling two different aspects of source quality. In so doing, ours is also the first approach designed to merge multi-valued attribute types. Our method is scalable, due to an efficient sampling-based inference algorithm that needs very few iterations in practice and enjoys linear time complexity, with an even faster incremental variant. Experiments on two real world datasets show that our new method outperforms existing state-of-the-art approaches to the truth finding problem.\n          <\/jats:p>","DOI":"10.14778\/2168651.2168656","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"550-561","source":"Crossref","is-referenced-by-count":262,"title":["A Bayesian approach to discovering truth from conflicting sources for data integration"],"prefix":"10.14778","volume":"5","author":[{"given":"Bo","family":"Zhao","sequence":"first","affiliation":[{"name":"University of Illinois, Urbana, IL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin I. P.","family":"Rubinstein","sequence":"additional","affiliation":[{"name":"Microsoft Research, Mountain View, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jim","family":"Gemmell","sequence":"additional","affiliation":[{"name":"Microsoft Research, Mountain View, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiawei","family":"Han","sequence":"additional","affiliation":[{"name":"University of Illinois, Urbana, IL"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2012,2]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/303976.303983"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963440"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/1883784.1883795"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687690"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687691"},{"key":"e_1_2_1_6_1","first-page":"216","volume-title":"VLDB","author":"Florescu D.","year":"1997","unstructured":"D. Florescu , D. Koller , and A. Y. Levy . Using probabilistic information in data integration . In VLDB , pages 216 -- 225 , 1997 . D. Florescu, D. Koller, and A. Y. Levy. Using probabilistic information in data integration. In VLDB, pages 216--225, 1997."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1718487.1718504"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1935826.1935896"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/324133.324140"},{"key":"e_1_2_1_10_1","first-page":"877","volume-title":"COLING","author":"Pasternack J.","year":"2010","unstructured":"J. Pasternack and D. Roth . Knowing what to believe (when you already know something) . In COLING , pages 877 -- 885 , 2010 . J. Pasternack and D. Roth. Knowing what to believe (when you already know something). In COLING, pages 877--885, 2010."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/2283696.2283785"},{"key":"e_1_2_1_12_1","volume-title":"Artificial Intelligence: A Modern Approach","author":"Russell S.","year":"2009","unstructured":"S. Russell and P. Norvig . Artificial Intelligence: A Modern Approach . Prentice Hall , 3 rd edition, 2009 . S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 3rd edition, 2009.","edition":"3"},{"key":"e_1_2_1_13_1","first-page":"7","volume-title":"DMSN","author":"Wang D.","year":"2011","unstructured":"D. Wang , T. Abdelzaher , L. Kaplan , and C. Aggarwal . On quantifying the accuracy of maximum likelihood estimation of participant reliability in social sensing . In DMSN , pages 7 -- 12 , 2011 . D. Wang, T. Abdelzaher, L. Kaplan, and C. Aggarwal. On quantifying the accuracy of maximum likelihood estimation of participant reliability in social sensing. In DMSN, pages 7--12, 2011."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1281192.1281309"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963439"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2168651.2168656","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:17:57Z","timestamp":1672219077000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2168651.2168656"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,2]]},"references-count":15,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2012,2]]}},"alternative-id":["10.14778\/2168651.2168656"],"URL":"https:\/\/doi.org\/10.14778\/2168651.2168656","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2012,2]]}}}