Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Online Generation of Association Rules
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Set-Oriented Mining for Association Rules in Relational Databases
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Aggregate-Query Processing in Data Warehousing Environments
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Information Retrieval from an Incomplete Data Cube
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Efficient runtime generation of association rules
Proceedings of the tenth international conference on Information and knowledge management
A Customer Purchase Incidence Model Applied to Recommender Services
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
Itemset Trees for Targeted Association Querying
IEEE Transactions on Knowledge and Data Engineering
Integrating Fuzziness into OLAP for Multidimensional Fuzzy Association Rules Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Employing OLAP mining for multiagent reinforcement learning
Design and application of hybrid intelligent systems
Pruning and Visualizing Generalized Association Rules in Parallel Coordinates
IEEE Transactions on Knowledge and Data Engineering
An efficient and flexible algorithm for online mining of large itemsets
Information Processing Letters
On Characterization and Discovery of Minimal Unexpected Patterns in Rule Discovery
IEEE Transactions on Knowledge and Data Engineering
Association mining in time-varying domains
Intelligent Data Analysis
Searching for high-support itemsets in itemset trees
Intelligent Data Analysis
An on-line interactive method for finding association rules data streams
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Discovering frequent itemsets by support approximation and itemset clustering
Data & Knowledge Engineering
On-line generation association rules over data streams
Information and Software Technology
Redundant association rules reduction techniques
International Journal of Business Intelligence and Data Mining
Online mining of fuzzy multidimensional weighted association rules
Applied Intelligence
Minimum-Size Bases of Association Rules
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Deduction Schemes for Association Rules
DS '08 Proceedings of the 11th International Conference on Discovery Science
RMAIN: Association rules maintenance without reruns through data
Information Sciences: an International Journal
An efficient and flexible algorithm for online mining of large itemsets
Information Processing Letters
Integrating fuzziness with OLAP association rules mining
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Automatic acquisition of phrase semantic rule for Chinese
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Toward boosting distributed association rule mining by data de-clustering
Information Sciences: an International Journal
Two measures of objective novelty in association rule mining
PAKDD'09 Proceedings of the 13th Pacific-Asia international conference on Knowledge discovery and data mining: new frontiers in applied data mining
Efficient prime-based method for interactive mining of frequent patterns
Expert Systems with Applications: An International Journal
Border algorithms for computing hasse diagrams of arbitrary lattices
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
A distributed knowledge extraction data mining algorithm
CIS'04 Proceedings of the First international conference on Computational and Information Science
Effective mining of fuzzy multi-cross-level weighted association rules
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Improved negative-border online mining approaches
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Redundant association rules reduction techniques
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Flexible online association rule mining based on multidimensional pattern relations
Information Sciences: an International Journal
PARAS: a parameter space framework for online association mining
Proceedings of the VLDB Endowment
PARAS: interactive parameter space exploration for association rule mining
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
FIRE: interactive visual support for parameter space-driven rule mining
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Formal and computational properties of the confidence boost of association rules
ACM Transactions on Knowledge Discovery from Data (TKDD)
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We discuss the problem of online mining of association rules in a large database of sales transactions. The online mining is performed by preprocessing the data effectively in order to make it suitable for repeated online queries. We store the preprocessed data in such a way that online processing may be done by applying a graph theoretic search algorithm whose complexity is proportional to the size of the output. The result is an online algorithm which is independent of the size of the transactional data and the size of the preprocessed data. The algorithm is almost instantaneous in the size of the output. The algorithm also supports techniques for quickly discovering association rules from large itemsets. The algorithm is capable of finding rules with specific items in the antecedent or consequent. These association rules are presented in a compact form, eliminating redundancy. The use of nonredundant association rules helps significantly in the reduction of irrelevant noise in the data mining process.