Data & Knowledge Engineering
Semantic integration of heterogeneous information sources
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Using Schema Matching to Simplify Heterogeneous Data Translation
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Database Schema Matching Using Machine Learning with Feature Selection
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Comparison of Schema Matching Evaluations
Revised Papers from the NODe 2002 Web and Database-Related Workshops on Web, Web-Services, and Database Systems
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Discovering Direct and Indirect Matches for Schema Elements
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
Attribute Classification Using Feature Analysis
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
iMAP: discovering complex semantic matches between database schemas
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Schema Matching Using Duplicates
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Clio grows up: from research prototype to industrial tool
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
HePToX: marrying XML and heterogeneity in your P2P databases
VLDB '05 Proceedings of the 31st international conference on Very large data bases
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A Flexible Approach for Planning Schema Matching Algorithms
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
Improving XML schema matching performance using Prüfer sequences
Data & Knowledge Engineering
Boosting Annotated Web Services in SAWSDL
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Rewrite techniques for performance optimization of schema matching processes
Proceedings of the 13th International Conference on Extending Database Technology
Semantic water data translation: a knowledge-driven approach
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
Element similarity measures in XML schema matching
Information Sciences: an International Journal
Discovering concept mappings by similarity propagation among substructures
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Reuse-oriented mapping discovery for meta-querier customization
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
On benchmarking data translation systems for semantic-web ontologies
Proceedings of the 20th ACM international conference on Information and knowledge management
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Matching Attributes across Overlapping Heterogeneous Data Sources Using Mutual Information
Journal of Database Management
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A common task in many database applications is the migration of legacy data from multiple sources into a new one. This requires identifying semantically related elements of the source and target systems and the creation of mapping expressions to transform instances of those elements from the source format to the target format. Currently, data migration is typically done manually, a tedious and timeconsuming process, which is difficult to scale to a high number of data sources. In this paper, we describe QuickMig, a new semi-automatic approach to determining semantic correspondences between schema elements for data migration applications. QuickMig advances the state of the art with a set of new techniques exploiting sample instances, domain ontologies, and reuse of existing mappings to detect not only element correspondences but also their mapping expressions. QuickMig further includes new mechanisms to effectively incorporate domain knowledge of users into the matching process. The results from a comprehensive evaluation using real-world schemas and data indicate the high quality and practicability of the overall approach.