Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
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
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 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
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Scalable Techniques for Mining Causal Structures
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
VLDB '99 Proceedings of the 25th 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
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Constraint-Based Rule Mining in Large, Dense Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Efficient Mining of Constrained Correlated Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
OPUS: an efficient admissible algorithm for unordered search
Journal of Artificial Intelligence Research
Integration of profile hidden Markov model output into association rule mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Mining itemset utilities from transaction databases
Data & Knowledge Engineering - Special issue: ER 2003
LCS-TRIM: dynamic programming meets XML indexing and querying
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Fast detection of database system abuse behaviors based on data mining approach
Proceedings of the 2nd international conference on Scalable information systems
Deriving strong association mining rules using a dependency criterion, the lift measure
International Journal of Data Analysis Techniques and Strategies
Emerging Cubes: Borders, size estimations and lossless reductions
Information Systems
Exact and Approximate Sizes of Convex Datacubes
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Reduced representations of Emerging Cubes for OLAP database mining
International Journal of Business Intelligence and Data Mining
MCFPTree: An FP-tree-based algorithm for multi-constraint patterns discovery
International Journal of Business Intelligence and Data Mining
Using a cosine-type measure to derive strong association mining rules
International Journal of Knowledge Engineering and Data Mining
uCFS2: an enhanced system that mines uncertain data for constrained frequent sets
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
Extracting semantics in OLAP databases using emerging cubes
Information Sciences: an International Journal
The discovery of frequent patterns with logic and constraint programming
MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control
An efficient itemset mining approach for data streams
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
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
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
A new class of constraints for constrained frequent pattern mining
Proceedings of the 27th Annual ACM Symposium on Applied Computing
A constrained frequent pattern mining system for handling aggregate constraints
Proceedings of the 16th International Database Engineering & Applications Sysmposium
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Constrained Cube Lattices for Multidimensional Database Mining
International Journal of Data Warehousing and Mining
20 years of pattern mining: a bibliometric survey
ACM SIGKDD Explorations Newsletter
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Recent work has highlighted the importance of the constraint-based mining paradigm in the context of frequent itemsets, associations, correlations, sequential patterns, and many other interesting patterns in large databases. Constraint pushing techniques have been developed for mining frequent patterns and associations with antimonotonic, monotonic, and succinct constraints. In this paper, we study constraints which cannot be handled with existing theory and techniques in frequent pattern mining. For example, avg(S)θv, median(S)θv, sum(S)θv (S can contain items of arbitrary values, θ ∈ {, v is a real number.) are customarily regarded as “tough” constraints in that they cannot be pushed inside an algorithm such as Apriori. We develop a notion of convertible constraints and systematically analyze, classify, and characterize this class. We also develop techniques which enable them to be readily pushed deep inside the recently developed FP-growth algorithm for frequent itemset mining. Results from our detailed experiments show the effectiveness of the techniques developed.