Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A database perspective on knowledge discovery
Communications of the ACM
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Generalization-based data mining in object-oriented databases using an object cube model
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Object Database Standard: ODMG-93, Release 1.2
Object Database Standard: ODMG-93, Release 1.2
Object-Oriented Database Systems: Concepts and Architectures
Object-Oriented Database Systems: Concepts and Architectures
SLIQ: A Fast Scalable Classifier for Data Mining
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
DBMiner: a system for data mining in relational databases and data warehouses
CASCON '97 Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative research
ISCC '97 Proceedings of the 2nd IEEE Symposium on Computers and Communications (ISCC '97)
A unified framework for heterogeneous patterns
Information Systems
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Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. The emerging data mining tools and systems lead to the demand of a powerful data mining query language. The concepts of such a language for relational databases are discussed before. With the increasing popularity of object-oriented databases, it is important to design a data mining query language for such databases. The main objective of this paper is to propose an Object Data Mining Query Language (ODMQL) for object-oriented databases as an extension to the Object Query Language (OQL) proposed by the Object Data Management Group (ODMG) as a standard query language for object-oriented databases. The proposed language is implemented as a feature of an experimental object-oriented database management system that is developed as a testbed for research issues of object-oriented databases.