Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Research problems in data warehousing
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 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
Online association rule mining
SIGMOD '99 Proceedings of the 1999 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
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Data mining: concepts and techniques
Data mining: concepts and techniques
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
A New Approach to Online Generation of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Synthesizing High-Frequency Rules from Different Data Sources
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
On Dual Mining: From Patterns to Circumstances, and Back
Proceedings of the 17th International Conference on Data Engineering
Computing Iceberg Queries Efficiently
VLDB '98 Proceedings of the 24rd 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
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Top Down FP-Growth for Association Rule Mining
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
A General Incremental Technique for Maintaining Discovered Association Rules
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
An Adaptive Algorithm for Incremental Mining of Association Rules
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
Constraint-Based Rule Mining in Large, Dense Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Efficient Indexing Structures for Mining Frequent Patterns
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Incremental, Online, and Merge Mining of Partial Periodic Patterns in Time-Series Databases
IEEE Transactions on Knowledge and Data Engineering
A new incremental data mining algorithm using pre-large itemsets
Intelligent Data Analysis
Mining spatial association rules in image databases
Information Sciences: an International Journal
An efficient algorithm for mining frequent inter-transaction patterns
Information Sciences: an International Journal
Efficient mining of weighted interesting patterns with a strong weight and/or support affinity
Information Sciences: an International Journal
Incremental and interactive mining of web traversal patterns
Information Sciences: an International Journal
Using data mining to increase customer life time value
AIC'06 Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications
An association-based case reduction technique for case-based reasoning
Information Sciences: an International Journal
The Mahalanobis-Taguchi system - Neural network algorithm for data-mining in dynamic environments
Expert Systems with Applications: An International Journal
Mining frequent trajectory patterns in spatial-temporal databases
Information Sciences: an International Journal
Sliding window-based frequent pattern mining over data streams
Information Sciences: an International Journal
RMAIN: Association rules maintenance without reruns through data
Information Sciences: an International Journal
Modeling a dynamic design system using the Mahalanobis Taguchi system: two-step optimal algorithm
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part III
Extracting semantics in OLAP databases using emerging cubes
Information Sciences: an International Journal
HUC-Prune: an efficient candidate pruning technique to mine high utility patterns
Applied Intelligence
Improved negative-border online mining approaches
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
An agent model for incremental rough set-based rule induction in customer relationship management
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Pattern mining of cloned codes in software systems
Information Sciences: an International Journal
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Most incremental mining and online mining algorithms concentrate on finding association rules or patterns consistent with entire current sets of data. Users cannot easily obtain results from only interesting portion of data. This may prevent the usage of mining from online decision support for multidimensional data. To provide ad-hoc, query-driven, and online mining support, we first propose a relation called the multidimensional pattern relation to structurally and systematically store context and mining information for later analysis. Each tuple in the relation comes from an inserted dataset in the database. We then develop an online mining approach called three-phase online association rule mining (TOARM) based on this proposed multidimensional pattern relation to support online generation of association rules under multidimensional considerations. The TOARM approach consists of three phases during which final sets of patterns satisfying various mining requests are found. It first selects and integrates related mining information in the multidimensional pattern relation, and then if necessary, re-processes itemsets without sufficient information against the underlying datasets. Some implementation considerations for the algorithm are also stated in detail. Experiments on homogeneous and heterogeneous datasets were made and the results show the effectiveness of the proposed approach.