The merge/purge problem for large databases
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Efficient clustering of high-dimensional data sets with application to reference matching
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Parallel Multilevel Graph Partitioning
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
Learning to match and cluster large high-dimensional data sets for data integration
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Record Linkage in Large Data Sets
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
Adaptive duplicate detection using learnable string similarity measures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Joint deduplication of multiple record types in relational data
Proceedings of the 14th ACM international conference on Information and knowledge management
Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Adaptive Blocking: Learning to Scale Up Record Linkage
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Object Identification with Constraints
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Entity Resolution with Markov Logic
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Learning blocking schemes for record linkage
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Learning to Extract Relations for Relational Classification
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Event-based classification of social media streams
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
An automatic blocking mechanism for large-scale de-duplication tasks
Proceedings of the 21st ACM international conference on Information and knowledge management
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Record linkage is a central task when information from different sources is integrated. Record linkage models use so-called blockers for reducing the search space by discarding obviously different record pairs. In practice, important problems have Zipf distributed class sizes with some large classes where blocking is not applicable any more. Therefore we propose two novel meta algorithms for scaling arbitrary record linkage models to such data sets. The first one parallelizes problems by creating overlapping subproblems and the second one reduces the search space for large classes effectively. Our evaluation shows that both scaling techniques are effective and are able to scale state-of-the-art models to challenging datasets.