C4.5: programs for machine learning
C4.5: programs for machine learning
Advances in knowledge discovery and data mining
Towards on-line analytical mining in large databases
ACM SIGMOD Record
A classification-based methodology for planning audit strategies in fraud detection
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining and Knowledge Discovery
Query Answering in Nondeterministic, Nonmonotonic Logic Databases
FQAS '98 Proceedings of the Third International Conference on Flexible Query Answering Systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Using Data Mining Techniques in Fiscal Fraud Detection
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
A classification-based methodology for planning audit strategies in fraud detection
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Nondeterministic, Nonmonotonic Logic Databases
IEEE Transactions on Knowledge and Data Engineering
Mining databases and data streams with query languages and rules
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
On Modal and Fuzzy Decision Logics Based on Rough Set Theory
Fundamenta Informaticae
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We introduce a Logic-Based Knowledge Discovery Support Environment, capable of integrating knowledge extraction and knowledge manipulation. Its flexibility and expressiveness in supporting the process of knowledge discovery in databases is illustrated by presenting two case studies, market-basket analysis and audit planning strategy in fraud detection. We show that the query language deals effectively and uniformly with data preparation, model extraction and model evaluation and analysis, thus providing a powerful formalism where methodologies for classes of challenging applications can be conveniently designed.