Attribute-oriented induction in data mining
Advances in knowledge discovery and data mining
Towards on-line analytical mining in large databases
ACM SIGMOD Record
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
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DBMiner is an online analytical mining system, developed for interactive mining of multiple-level knowledge in large relational databases and data warehouses (see Chapters 6.1 and 13). The distinct feature of the system is its tight integration of online analytical processing (OLAP) with a wide spectrum of data mining functions, including characterization, association, classification, prediction, and clustering (see Chapters 16.1, 16.2.2, 16.2.3 and 16.5). The system facilitates query-based, interactive mining of multidimensional databases (see Chapter 6.3) by implementing a set of advanced data mining techniques, including OLAP-based induction, multidimensional statistical analysis, progressive deepening for mining refined knowledge, meta-rule guided mining, and data and knowledge visualization (see Chapter 20). DBMiner integrates smoothly with commercial relational database and data warehouse systems, and provides a user-friendly, interactive data mining environment with high performance. With extensions to the DBMiner system, several specialized data mining system prototypes, including GeoMiner, MultiMediaMiner, and WeblogMiner, have been designed and developed for mining complex types of data with interesting applications.