{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T04:08:36Z","timestamp":1759205316465,"version":"3.41.0"},"reference-count":39,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2006,3,1]],"date-time":"2006-03-01T00:00:00Z","timestamp":1141171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Database Syst."],"published-print":{"date-parts":[[2006,3]]},"abstract":"<jats:p>\n            To enable information integration, schema matching is a critical step for discovering semantic correspondences of attributes across heterogeneous sources. While complex matchings are common, because of their far more complex search space, most existing techniques focus on simple 1:1 matchings. To tackle this challenge, this article takes a conceptually novel approach by viewing schema matching as\n            <jats:italic>correlation mining<\/jats:italic>\n            , for our task of matching Web query interfaces to integrate the myriad databases on the Internet. On this \u201cdeep Web \u201d query interfaces generally form\n            <jats:italic>complex matchings<\/jats:italic>\n            between attribute groups (e.g., {author} corresponds to {first name, last name} in the Books domain). We observe that the co-occurrences patterns across query interfaces often reveal such complex semantic relationships:\n            <jats:italic>grouping attributes<\/jats:italic>\n            (e.g., {first name, last name}) tend to be co-present in query interfaces and thus positively correlated. In contrast,\n            <jats:italic>synonym attributes<\/jats:italic>\n            are negatively correlated because they rarely co-occur. This insight enables us to discover complex matchings by a correlation mining approach. In particular, we develop the DCM framework, which consists of\n            <jats:italic>data preprocessing<\/jats:italic>\n            ,\n            <jats:italic>dual mining<\/jats:italic>\n            of positive and negative correlations, and finally\n            <jats:italic>matching construction<\/jats:italic>\n            . We evaluate the DCM framework on manually extracted interfaces and the results show good accuracy for discovering complex matchings. Further, to automate the entire matching process, we incorporate automatic techniques for interface extraction. Executing the DCM framework on automatically extracted interfaces, we find that the inevitable errors in automatic interface extraction may significantly affect the matching result. To make the DCM framework robust against such \u201cnoisy\u201d schemas, we integrate it with a novel \u201censemble\u201d approach, which creates an ensemble of DCM matchers, by randomizing the schema data into many\n            <jats:italic>trials<\/jats:italic>\n            and aggregating their ranked results by taking majority voting. As a principled basis, we provide analytic justification of the robustness of the ensemble approach. Empirically, our experiments show that the \u201censemblization\u201d indeed significantly boosts the matching accuracy, over automatically extracted and thus noisy schema data. By employing the DCM framework with the ensemble approach, we thus complete an automatic process of matchings Web query interfaces.\n          <\/jats:p>","DOI":"10.1145\/1132863.1132872","type":"journal-article","created":{"date-parts":[[2006,7,25]],"date-time":"2006-07-25T14:14:26Z","timestamp":1153836866000},"page":"346-395","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":58,"title":["Automatic complex schema matching across Web query interfaces"],"prefix":"10.1145","volume":"31","author":[{"given":"Bin","family":"He","sequence":"first","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kevin Chen-Chuan","family":"Chang","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2006,3]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/170035.170072"},{"key":"e_1_2_1_2_1","unstructured":"Anderson D. 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Computer Science Department University of Illinois at Urbana-Champaign. http:\/\/metaquerier.cs.uiuc.edu\/repository.]]"},{"volume-title":"Proceedings of the CIDR 2005 Conference.]]","author":"Chang K. C.-C.","key":"e_1_2_1_11_1","unstructured":"Chang , K. C.-C. , He , B. , and Zhang , Z . 2005. Toward large scale integration: Building a metaquerier over databases on the web . In Proceedings of the CIDR 2005 Conference.]] Chang, K. C.-C., He, B., and Zhang, Z. 2005. Toward large scale integration: Building a metaquerier over databases on the web. 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