Discovering matching dependencies
Proceedings of the 18th ACM conference on Information and knowledge management
Reasoning about record matching rules
Proceedings of the VLDB Endowment
EIF: a framework of effective entity identification
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Record linkage with uniqueness constraints and erroneous values
Proceedings of the VLDB Endowment
Differential dependencies: Reasoning and discovery
ACM Transactions on Database Systems (TODS)
Dynamic constraints for record matching
The VLDB Journal — The International Journal on Very Large Data Bases
Comparable dependencies over heterogeneous data
The VLDB Journal — The International Journal on Very Large Data Bases
Editorial: Efficient discovery of similarity constraints for matching dependencies
Data & Knowledge Engineering
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When merging data from various sources, it is often the case that small variations in data format and interpretation cause traditional functional dependencies (FDs) to be violated, without there being an intrinsic violation of semantics. Examples include differing address formats, or different reported latitude/longitudes for a given address. In this paper, we define metric functional dependencies, which strictly generalize traditional FDs by allowing small differences (controlled by a metric) in values of the consequent attribute of an FD. We present efficient algorithms for the verification problem: determining whether a given metric FD holds for a given relation. We experimentally demonstrate the validity and efficiency of our approach on various data sets that lie in multidimensional spaces.