The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
A database perspective on knowledge discovery
Communications of the ACM
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Optimization of constrained frequent set queries with 2-variable constraints
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Can we push more constraints into frequent pattern mining?
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: concepts and techniques
Data mining: concepts and techniques
Molecular feature mining in HIV data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
MSQL: A Query Language for Database Mining
Data Mining and Knowledge Discovery
A Tightly-Coupled Architecture for Data Mining
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
On Dual Mining: From Patterns to Circumstances, and Back
Proceedings of the 17th International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
DualMiner: a dual-pruning algorithm for itemsets with constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Adaptive and Resource-Aware Mining of Frequent Sets
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
ExAMiner: Optimized Level-wise Frequent Pattern Mining with Monotone Constraints
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
On Closed Constrained Frequent Pattern Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Answering constraint-based mining queries on itemsets using previous materialized results
Journal of Intelligent Information Systems
Soft constraint based pattern mining
Data & Knowledge Engineering
Integrating pattern mining in relational databases
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Pushing tougher constraints in frequent pattern mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Extending the soft constraint based mining paradigm
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
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In this paper we present ConQueSt, a constraint based querying system devised with the aim of supporting the intrinsically exploratory (i.e., human-guided, interactive, iterative) nature of pattern discovery. Following the inductive database vision, our framework provides users with an expressive constraint based query language which allows the discovery process to be effectively driven toward potentially interesting patterns. Such constraints are also exploited to reduce the cost of pattern mining computation. We implemented a comprehensive mining system that can access real world relational databases from which extract data. After a preprocessing step, mining queries are answered by an efficient pattern mining engine which entails several data and search space reduction techniques. Resulting patterns are then presented to the user, and possibly stored in the database. New user-defined constraints can be easily added to the system in order to target the particular application considered.