Applied categorical data analysis
Applied categorical data analysis
Applied multivariate statistical analysis
Applied multivariate statistical analysis
A probabilistic relational data model
EDBT '90 Proceedings of the 2nd international conference on extending database technology: Advances in Database Technology
Processing time-constrained aggregate queries in CASE-DB
ACM Transactions on Database Systems (TODS)
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Imprecise and Uncertain Information in Databases: An Evidential Approach
Proceedings of the Eighth International Conference on Data Engineering
Relational Databases with Exclusive Disjunctions
Proceedings of the Eighth International Conference on Data Engineering
An Interval Classifier for Database Mining Applications
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Knowledge Discovery in Databases: An Attribute-Oriented Approach
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Implementation and management of a mobile phone filtering system
International Journal of Network Management
An intelligent middleware for linear correlation discovery
Decision Support Systems
Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
On Information-Theoretic Measures of Attribute Importance
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Linear correlation discovery in databases: a data mining approach
Data & Knowledge Engineering
Checks and balances: monitoring data quality problems in network traffic databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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In this paper, we discuss modeling and extraction of statistical relationships among attributes. Different methods are used for extraction of different types of relationships. A complete methodology for extraction is developed by integrating widely accepted statistical methods. Statistical relationships manifest embedded relationships in data and thus lend themselves naturally to estimating unknown attribute values and detecting unlikely values. We will carefully examine these applications and evaluate the usefulness of statistical relationships in these applications using a real-life database.