Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
Language features for interoperability of databases with schematic discrepancies
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Information-based objective functions for active data selection
Neural Computation
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Machine Learning
Automatic thesaurus construction using Bayesian networks
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
The TSIMMIS Approach to Mediation: Data Models and Languages
Journal of Intelligent Information Systems - Special issue: next generation information technologies and systems
Multidatabase query processing with uncertainty in global keys and attribute values
Journal of the American Society for Information Science - Special issue: management of imprecision and uncertainty
Your mediators need data conversion!
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Database techniques for the World-Wide Web: a survey
ACM SIGMOD Record
Data & Knowledge Engineering
Data-driven understanding and refinement of schema mappings
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Towards a theory of natural language interfaces to databases
Proceedings of the 8th international conference on Intelligent user interfaces
Correspondence and Translation for Heterogeneous Data
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Active Learning for Natural Language Parsing and Information Extraction
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Optimizing Queries Across Diverse Data Sources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Using Schema Matching to Simplify Heterogeneous Data Translation
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Schema Mapping as Query Discovery
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Visual Web Information Extraction with Lixto
Proceedings of the 27th International Conference on Very Large Data Bases
RoadRunner: Towards Automatic Data Extraction from Large Web Sites
Proceedings of the 27th International Conference on Very Large Data Bases
Querying Heterogeneous Information Sources Using Source Descriptions
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
SchemaSQL - A Language for Interoperability in Relational Multi-Database Systems
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Describing and Using Query Capabilities of Heterogeneous Sources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Accessing Heterogeneous Data Through Homogenization and Integration Mediators
COOPIS '97 Proceedings of the Second IFCIS International Conference on Cooperative Information Systems
A Meta-Wrapper for Scaling up to Multiple Autonomous Distributed Information Sources
COOPIS '98 Proceedings of the 3rd IFCIS International Conference on Cooperative Information Systems
Selective Sampling with Redundant Views
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Scaling heterogeneous databases and the design of Disco
ICDCS '96 Proceedings of the 16th International Conference on Distributed Computing Systems (ICDCS '96)
A Schema Analysis and Reconciliation Tool Environment for Heterogeneous Databases
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Version spaces: an approach to concept learning.
Version spaces: an approach to concept learning.
Programming by Demonstration Using Version Space Algebra
Machine Learning
iMAP: discovering complex semantic matches between database schemas
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Automatic thesaurus construction based on grammatical relations
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Translating SQL Applications to the Semantic Web
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
Challenges and conflicts integrating heterogeneous data warehouses in virtual organisations
International Journal of Networking and Virtual Organisations
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The Internet has instigated a critical need for automated tools that facilitate integrating countless databases. Since nontechnical end users are often the ultimate repositories of the domain information required to distinguish differences in data types, an effective solution must integrate simple GUI based data browsing tools and automatic mapping methods that eliminate the requirement for a technical user to supervise the process. We develop a metamodel of data integration as the basis for absorbing feedback from an end user. The schema integration algorithm draws examples from the data and learns integrating view definitions by asking a user simple yes or no questions. The metamodel enables a search mechanism that is guaranteed to converge to a correct integrating view definition without the user having to know a view definition language such as SQL or SchemaSQL, or even having to inspect the final view definition. We show how data catalog statistics, normally used to optimize queries, can be exploited to parameterize the search heuristics and improve the convergence of the learning algorithm.