Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic similarity networks
Probabilistic similarity networks
C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Cost-based abduction and MAP explanation
Artificial Intelligence
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
IEEE Transactions on Knowledge and Data Engineering
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Discovering Structural Association of Semistructured Data
IEEE Transactions on Knowledge and Data Engineering
Visualization Support for Data Mining
IEEE Expert: Intelligent Systems and Their Applications
Computational properties of metaquerying problems
ACM Transactions on Computational Logic (TOCL)
Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Towards Efficient Metaquerying
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Amortization, lazy evaluation, and persistence: lists with catenation via lazy linking
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Discovering Associations in XML Data
WISEW '02 Proceedings of the Third International Conference on Web Information Systems Engineering (Workshops) - (WISEw'02)
Metaqueries: semantics, complexity, and efficient algorithms
Artificial Intelligence
Cost-sharing in Bayesian knowledge bases
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
KDDML: a middleware language and system for knowledge discovery in databases
Data & Knowledge Engineering
Enumerating consistent metaquery instantiations
AI Communications
On automatic knowledge validation for Bayesian knowledge bases
Data & Knowledge Engineering
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FlexiMine is a KDD system designed as a testbed for data-mining research, as well as a generic knowledge discovery tool for varied database domains. Flexibility is achieved by an open-ended design for extensibility, thus enabling integration of existing data-mining algorithms, new locally developed algorithms, and utility functions such as visualization and preprocessing. Support for new databases is simple and clean: the system interfaces with a standard database server via SQL queries and thus can handle any application database. With a view of serving remote, as well as local, users, internet availability was a design goal. By implementing the system in Java, minor modifications allow us to run the user-end of the system either as a Java applications or (with some limitations on the user) as a Java Applet. This paper reviews the architecture, design and operation of FlexiMine and presents some of the new ideas incorporated in the data-mining algorithms (Association rules, Decision trees, Bayesian knowledge-bases and Meta-queries).