{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/16095"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/16095","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Developing, tuning, and using schema matching systems","abstract":"This dissertation studies the schema matching problem that finds semantic correspon- dences (called matches) between disparate data sources. Examples of semantic matches include “location = address” and “name = concat(first-name,last-name).” Schema matching is one of the key challenges for many data sharing and exchange applications. Prime examples of such applications arise in numerous contexts, including data warehousing, scientific collaboration, e-commerce, bioinformatics, and data integra- tion on the World Wide Web. Despite significant progress, many challenges remain. These include discovering complex matches, a prevalent problem in practice, tuning a matching system, and deploying a matching system effectively in an application. In this dissertation, we develop solutions for the three challenges mentioned above. First, we develop a system that discovers both one-to-one and complex matches and pro- vides a novel explanation facility that helps users analyze matches. Next, we develop a framework that automatically tunes multi-component matching systems by synthesiz- ing a collection of matching scenarios. Finally, we show that we can efficiently exploit discovered semantic matches without extra user effort in certain applications.","abstract_html":"This dissertation studies the schema matching problem that finds semantic correspon- dences (called matches) between disparate data sources. Examples of semantic matches include “location = address” and “name = concat(first-name,last-name).” Schema matching is one of the key challenges for many data sharing and exchange applications. Prime examples of such applications arise in numerous contexts, including data warehousing, scientific collaboration, e-commerce, bioinformatics, and data integra- tion on the World Wide Web. Despite significant progress, many challenges remain. These include discovering complex matches, a prevalent problem in practice, tuning a matching system, and deploying a matching system effectively in an application. In this dissertation, we develop solutions for the three challenges mentioned above. First, we develop a system that discovers both one-to-one and complex matches and pro- vides a novel explanation facility that helps users analyze matches. Next, we develop a framework that automatically tunes multi-component matching systems by synthesiz- ing a collection of matching scenarios. Finally, we show that we can efficiently exploit discovered semantic matches without extra user effort in certain applications.","abstract_has_math":false,"creators":["Lee, Yoonkyong"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Doan, AnHai","Belford, Geneva G.","Winslett, Marianne","Zhai, ChengXiang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-05-19T18:34:43Z","date_published":"2010-05-19T18:34:43Z","updated_at":"2026-07-22T22:25:08Z","subjects":["schema matching","data integration"],"languages":["en"],"rights":["Copyright 2010 Yoonkyong Lee"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/16095","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Doan, AnHai","Belford, Geneva G.","Winslett, Marianne","Zhai, ChengXiang"]},{"key":"dc:creator","label":"Author","values":["Lee, Yoonkyong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2010-05-19T18:34:43Z","2010-5"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["schema matching","data integration"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2010 Yoonkyong Lee"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/16095"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation studies the schema matching problem that finds semantic correspon- dences (called matches) between disparate data sources. 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