Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Association rules over interval data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Discovering roll-up dependencies
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: concepts and techniques
Data mining: concepts and techniques
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Editorial: Efficient discovery of similarity constraints for matching dependencies
Data & Knowledge Engineering
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We introduce the construct of neighborhood dependency (ND) to express regularities like: "Families with similar size and income, tend to own cars of similar size." Arguably, the discovery of such regularities is useful for prediction purposes. We have implemented and tested an algorithm for mining NDs. The discovered NDs are then used in the P-neighborhood method to predict unknown values.