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
Can we push more constraints into frequent pattern mining?
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Efficient Mining of Constrained Correlated Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Efficient Mining of Constrained Frequent Patterns from Streams
IDEAS '06 Proceedings of the 10th International Database Engineering and Applications Symposium
Efficient Mining of Frequent Patterns from Uncertain Data
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Finding frequent items in probabilistic data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Clustering Uncertain Data Via K-Medoids
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
A constraint-based querying system for exploratory pattern discovery
Information Systems
Mining frequent patterns in image databases with 9D-SPA representation
Journal of Systems and Software
Mining of Frequent Itemsets from Streams of 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
Summary queries for frequent itemsets mining
Journal of Systems and Software
Mining association rules with multi-dimensional constraints
Journal of Systems and Software
Mining frequent itemsets from uncertain data
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Mining uncertain data for frequent itemsets that satisfy aggregate constraints
Proceedings of the 2010 ACM Symposium on Applied Computing
A decremental approach for mining frequent itemsets from uncertain data
PAKDD'08 Proceedings of the 12th 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
Mining uncertain data with probabilistic guarantees
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
uCFS2: an enhanced system that mines uncertain data for constrained frequent sets
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
Mining fuzzy association rules from uncertain data
Knowledge and Information Systems
New and efficient knowledge discovery of partial periodic patterns with multiple minimum supports
Journal of Systems and Software
Adjusting Fuzzy Similarity Functions for use with standard data mining tools
Journal of Systems and Software
Mining frequent patterns from univariate uncertain data
Data & Knowledge Engineering
Stream mining on univariate uncertain data
Applied Intelligence
| Hi-index | 0.00 |
In this paper, we propose a new algorithm called CUP-Miner (Constrained Univariate Uncertain Data Pattern Miner) for mining frequent patterns from univariate uncertain data under user-specified constraints. The discovered frequent patterns are called constrained frequent U2 patterns (where ''U2'' represents ''univariate uncertain''). In univariate uncertain data, each attribute in a transaction is associated with a quantitative interval and a probability density function. The CUP-Miner algorithm is implemented in two phases: In the first phase, a U2P-tree (Univariate Uncertain Pattern tree) is constructed by compressing the target database transactions into a compact tree structure. Then, in the second phase, the constrained frequent U2 pattern is enumerated by traversing the U2P-tree with different strategies that correspond to different types of constraints. The algorithm speeds up the mining process by exploiting five constraint properties: succinctness, anti-monotonicity, monotonicity, convertible anti-monotonicity, and convertible monotonicity. Our experimental results demonstrate that CUP-Miner outperforms the modified CAP algorithm, the modified FIC algorithm, the modified U2P-Miner algorithm, and the modified Apriori algorithm.