Partially Supervised Classification of Text Documents
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
PEBL: positive example based learning for Web page classification using SVM
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning domain-independent string transformation weights for high accuracy object identification
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
TAILOR: A Record Linkage Tool Box
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Adaptive duplicate detection using learnable string similarity measures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Methods for evaluating and creating data quality
Information Systems - Special issue: Data quality in cooperative information systems
Quality Measures in Data Mining (Studies in Computational Intelligence)
Quality Measures in Data Mining (Studies in Computational Intelligence)
A two-step classification approach to unsupervised record linkage
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Febrl: a freely available record linkage system with a graphical user interface
HDKM '08 Proceedings of the second Australasian workshop on Health data and knowledge management - Volume 80
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Probabilistic data generation for deduplication and data linkage
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
Automatic record linkage using seeded nearest neighbour and support vector machine classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Geocode Matching and Privacy Preservation
Privacy, Security, and Trust in KDD
ACM SIGKDD Explorations Newsletter
Frameworks for entity matching: A comparison
Data & Knowledge Engineering
Multiple valued logic approach for matching patient records in multiple databases
Journal of Biomedical Informatics
Multiple instance learning for group record linkage
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
A supervised learning and group linking method for historical census household linkage
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
| Hi-index | 0.00 |
Linking records from two or more databases is an increasingly important data preparation step in many data mining projects, as linked data can enable studies that are not feasible otherwise, or that would require expensive collection of specific data. The aim of such linkages is to match all records that refer to the same entity. One of the main challenges in record linkage is the accurate classification of record pairs into matches and non-matches. Many modern classification techniques are based on supervised machine learning and thus require training data, which is often not available in real world situations. A novel two-step approach to unsupervised record pair classification is presented in this paper. In the first step, training examples are selected automatically, and they are then used in the second step to train a binary classifier. An experimental evaluation shows that this approach can outperform k-means clustering and also be much faster than other classification techniques.