Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A database perspective on knowledge discovery
Communications of the ACM
Advances in knowledge discovery and data mining
Towards on-line analytical mining in large databases
ACM SIGMOD Record
Query flocks: a generalization of association-rule mining
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Integrating association rule mining with relational database systems: alternatives and implications
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
Query driven knowledge discovery in multidimensional data
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 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
Principles of data mining
Molecular feature mining in HIV data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Relational Data Mining
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
DMajor—Application Programming Interface for Database Mining
Data Mining and Knowledge Discovery
MSQL: A Query Language for Database Mining
Data Mining and Knowledge Discovery
IEEE Transactions on Knowledge and Data Engineering
Set-Oriented Mining for Association Rules in Relational Databases
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
A Tightly-Coupled Architecture for Data Mining
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Querying Inductive Databases via Logic-Based User-Defined Aggregates
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
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
Enhancing the Apriori Algorithm for Frequent Set Counting
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
DLAB: A Declarative Language Bias Formalism
ISMIS '96 Proceedings of the 9th International Symposium on Foundations of Intelligent Systems
Making Knowledge Extraction and Reasoning Closer
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
A Logical Database Mining Query Language
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
DualMiner: a dual-pruning algorithm for itemsets with constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Query Optimization to Support Data Mining
DEXA '97 Proceedings of the 8th International Workshop on Database and Expert Systems Applications
Adaptive and Resource-Aware Mining of Frequent Sets
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Frequent-Pattern based Iterative Projected Clustering
ICDM '03 Proceedings of the Third 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
MaPle: A Fast Algorithm for Maximal Pattern-based Clustering
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Specifying Mining Algorithms with Iterative User-Defined Aggregates
IEEE Transactions on Knowledge and Data Engineering
On Closed Constrained Frequent Pattern Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Efficient breadth-first mining of frequent pattern with monotone constraints
Knowledge and Information Systems
On condensed representations of constrained frequent patterns
Knowledge and Information Systems
Optimization of association rule mining queries
Intelligent Data Analysis
The levelwise version space algorithm and its application to molecular fragment finding
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Pushing tougher constraints in frequent pattern mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Integer linear programming models for constrained clustering
DS'10 Proceedings of the 13th international conference on Discovery science
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As a step towards the design of an Inductive Database System, in this paper we present a primitive for constraint-based frequent pattern mining, which represents a careful trade-off between expressiveness and efficiency. Such primitive is a simple mechanism which takes a relational table in input and extracts from it all frequent patterns which satisfy a given set of user-defined constraints. Despite its simplicity, the proposed primitive is expressive enough to deal with a broad range of interesting constraint-based frequent pattern queries,using a comprehensive repertoire of constraints defined over SQL aggregates. Thanks to its simplicity, the proposed primitive is amenable to be smoothly embedded in a variety of data mining query languages and be efficiently executed, by the state-of-the-art optimization techniques based on pushing the various form of constraints by means of data reduction.