Developing, tuning, and using schema matching systems

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2010

Author dc:creator

• Lee, Yoonkyong

Contributors dc:contributor

• Doan, AnHai
• Belford, Geneva G.
• Winslett, Marianne
• Zhai, ChengXiang

• schema matching
• data integration

Statement dc:rights

• Copyright 2010 Yoonkyong Lee

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/16095

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/16095