A knowledge-based approach for duplicate elimination in data cleaning
Information Systems - Data extraction, cleaning and reconciliation
Large-Scale Deduplication with Constraints Using Dedupalog
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Combining a Logical and a Numerical Method for Data Reconciliation
Journal on Data Semantics XII
Discovering and Maintaining Links on the Web of Data
ISWC '09 Proceedings of the 8th International Semantic Web Conference
KD2R: a key discovery method for semantic reference reconciliation
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems
EAGLE: efficient active learning of link specifications using genetic programming
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Learning expressive linkage rules using genetic programming
Proceedings of the VLDB Endowment
Keys and pseudo-keys detection for web datasets cleansing and interlinking
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
Data Linking for the Semantic Web
International Journal on Semantic Web & Information Systems
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KD2R allows the automatic discovery of composite key constraints in RDF data sources that conform to a given ontology. We consider data sources for which the Unique Name Assumption is fulfilled. KD2R allows this discovery without having to scan all the data. Indeed, the proposed system looks for maximal non keys and derives minimal keys from this set of non keys. KD2R has been tested on several datasets available on the web of data and it has obtained promising results when the discovered keys are used to link data. In the demo, we will demonstrate the functionality of our tool and we will show on several datasets that the keys can be used in a datalinking tool.