Handbook of record linkage: methods for health and statistical studies, administration, and business
Handbook of record linkage: methods for health and statistical studies, administration, and business
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
C4.5: programs for machine learning
C4.5: programs for machine learning
String searching algorithms
Identifying object isomerism in multidatabase systems
Distributed and Parallel Databases
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Automating the approximate record-matching process
Information Sciences—Informatics and Computer Science: An International Journal
Machine Learning
Learning object identification rules for information integration
Information Systems - Data extraction, cleaning and reconciliation
Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem
Data Mining and Knowledge Discovery
Reducing Inconsistency in Integrating Data From Different Sources
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Entity Matching in Heterogeneous Databases: A Distance Based Decision Model
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
Semantic matching across heterogeneous data sources
Communications of the ACM - The patent holder's dilemma: buy, sell, or troll?
Combining schema and instance information for integrating heterogeneous data sources
Data & Knowledge Engineering
Exploring Attribute Correspondences Across Heterogeneous Databases by Mutual Information
Journal of Management Information Systems
An approach to XML path matching
Proceedings of the 9th annual ACM international workshop on Web information and data management
Data & Knowledge Engineering
Exploiting context analysis for combining multiple entity resolution systems
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
The Normalized Compression Distance as a Distance Measure in Entity Identification
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
Frameworks for entity matching: A comparison
Data & Knowledge Engineering
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
Constructing a decision support system for management of employee turnover risk
Information Technology and Management
Quality-aware similarity assessment for entity matching in Web data
Information Systems
Scaling multiple-source entity resolution using statistically efficient transfer learning
Proceedings of the 21st ACM international conference on Information and knowledge management
Automatic SLA Matching and Provider Selection in Grid and Cloud Computing Markets
GRID '12 Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing
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Entity identification, i.e., detecting semantically corresponding records from heterogeneous data sources, is a critical step in integrating the data sources. The objective of this research is to develop and evaluate a novel multiple classifier system approach that improves entity identification accuracy. We apply various classification techniques drawn from statistical pattern recognition, machine learning, and artificial neural networks to determine whether two records from different data sources represent the same real-world entity. We further employ a variety of ways to combine multiple classifiers for improved classification accuracy. In this paper, we report on some promising empirical results that demonstrate performance improvement by combining multiple classifiers.