Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data
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
Efficiently mining long patterns from databases
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
Efficient mining of association rules using closed itemset lattices
Information Systems
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Data mining on an OLTP system (nearly) for free
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Turbo-charging vertical mining of large databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A tree projection algorithm for generation of frequent item sets
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Parallel Algorithms for Discovery of Association Rules
Data Mining and Knowledge Discovery
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
A Tight Upper Bound on the Number of Candidate Patterns
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Predictive Load Control for Flexible Buffer Allocation
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Managing Memory to Meet Multiclass Workload Response Time Goals
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Memory-Adaptive External Sorting
VLDB '93 Proceedings of the 19th 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
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Efficient Mining for Association Rules with Relational Database Systems
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Mining association rules in very large clustered domains
Information Systems
RMAIN: Association rules maintenance without reruns through data
Information Sciences: an International Journal
Collocation pattern mining in a limited memory environment using materialized iCPI-tree
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Self-configuring data mining for ubiquitous computing
Information Sciences: an International Journal
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New application areas resulted in an increase of the diversity of the workloads that Data Base Management Systems have to confront. Resource management for mixed workloads is attained with the prioritization of their tasks, which during their execution may be forced to release some of their resources. In this paper, we consider workloads that consist of mixtures of OLTP transactions and association rule mining queries. We propose and evaluate a new scheme for memory-adaptive association rule mining. It is designed to be used in the case of memory fluctuations, which are due to OLTP transactions that run with higher priority. The proposed scheme uses dynamic adjustment to the provided buffer space. Thus, it avoids the drawbacks of simple but naive approaches; namely the thrashing due to large disk accesses that can be caused by the direct use of virtual memory or long delay times due to suspension. Detailed experimental results, which consider a wide range of factors, indicate the superiority of the proposed scheme.