Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 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
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Constraint-Based Rule Mining in Large, Dense Databases
Data Mining and Knowledge Discovery
Mining Frequent Item Sets with Convertible Constraints
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
Efficient Mining of Constrained Correlated Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Efficient dynamic mining of constrained frequent sets
ACM Transactions on Database Systems (TODS)
A probability analysis for candidate-based frequent itemset algorithms
Proceedings of the 2006 ACM symposium on Applied computing
Looking for monotonicity properties of a similarity constraint on sequences
Proceedings of the 2006 ACM symposium on Applied computing
Maintenance of maximal frequent itemsets in large databases
Proceedings of the 2007 ACM symposium on Applied computing
Mining itemsets in the presence of missing values
Proceedings of the 2007 ACM symposium on Applied computing
Optimizing hypergraph transversal computation with an anti-monotone constraint
Proceedings of the 2007 ACM symposium on Applied computing
Frequent pattern mining for kernel trace data
Proceedings of the 2008 ACM symposium on Applied computing
Mining fault-tolerant frequent patterns efficiently with powerful pruning
Proceedings of the 2008 ACM symposium on Applied computing
Finding frequent items in probabilistic data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Frequent spatio-temporal patterns in trajectory data warehouses
Proceedings of the 2009 ACM symposium on Applied Computing
A Framework for Clustering Uncertain Data Streams
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Probabilistic Verifiers: Evaluating Constrained Nearest-Neighbor Queries over Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Mining of Frequent Itemsets from Streams of Uncertain Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Decision Trees for Uncertain Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Frequent pattern mining with uncertain data
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic frequent itemset mining in uncertain databases
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient algorithms for mining constrained frequent patterns from uncertain data
Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data
Mining uncertain data for constrained frequent sets
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Mining frequent itemsets from uncertain data
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
A tree-based approach for frequent pattern mining from uncertain data
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Probabilistic spatial queries on existentially uncertain data
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
uCFS2: an enhanced system that mines uncertain data for constrained frequent sets
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
Frequent itemset mining of uncertain data streams using the damped window model
Proceedings of the 2011 ACM Symposium on Applied Computing
Equivalence class transformation based mining of frequent itemsets from uncertain data
Proceedings of the 2011 ACM Symposium on Applied Computing
Distributed mining of constrained frequent sets from uncertain data
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
A new class of constraints for constrained frequent pattern mining
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Constrained frequent pattern mining on univariate uncertain data
Journal of Systems and Software
Stream mining of frequent sets with limited memory
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Discovering frequent itemsets on uncertain data: a systematic review
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
| Hi-index | 0.00 |
Many existing algorithms mine transaction databases of precise data for frequent itemsets. However, there are situations in which the user is interested in only some tiny portions of all the frequent itemsets, and there are also situations in which data in the transaction databases are uncertain. This calls for both (i) constrained mining (for finding only those frequent itemsets that satisfy user constraints, which express the user interest) and (ii) mining uncertain data. In this paper, we propose a tree-based algorithm that effectively mines transaction databases of uncertain data for only those frequent itemsets satisfying the user-specified aggregate constraints. The algorithm avoids candidate generation and pushes the aggregate constraints inside the mining process, which reduces computation and avoids unnecessary constraint checking.