Artificial Intelligence
Journal of Complexity
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 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
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Probabilistic logic programming with conditional constraints
ACM Transactions on Computational Logic (TOCL)
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Mining All Non-derivable Frequent Itemsets
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
A probability analysis for candidate-based frequent itemset algorithms
Proceedings of the 2006 ACM symposium on Applied computing
Computational complexity of queries based on itemsets
Information Processing Letters
Assessing data mining results via swap randomization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Itemset frequency satisfiability: Complexity and axiomatization
Theoretical Computer Science
Anonymity preserving pattern discovery
The VLDB Journal — The International Journal on Very Large Data Bases
Recognizing unexpected recurrence behaviors with fuzzy measures in sequence databases
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Computational complexity of queries based on itemsets
Information Processing Letters
Privacy-preserving frequent pattern sharing
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
ACM Transactions on Database Systems (TODS)
A further study on inverse frequent set mining
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
A FP-tree-based method for inverse frequent set mining
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
Transaction databases, frequent itemsets, and their condensed representations
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
FoIKS'12 Proceedings of the 7th international conference on Foundations of Information and Knowledge Systems
Tractable reasoning problems with fully-characterized association rules
ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
Bands of privacy preserving objectives: classification of PPDM strategies
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Solving inverse frequent itemset mining with infrequency constraints via large-scale linear programs
ACM Transactions on Knowledge Discovery from Data (TKDD)
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Computing frequent itemsets is one of the most prominent problems in data mining. We introduce a new, related problem, called FREQSAT: given some itemset-interval pairs, does there exist a database such that for every pair the frequency of the itemset falls in the interval? It is shown in this paper that FREQSAT is not finitely axiomatizable and that it is NP-complete. We also study cases in which other characteristics of the database are given as well. These characteristics can complicate FREQSAT even more. For example, when the maximal number of duplicates of a transaction is known, FREQSAT becomes PP-hard. We describe applications of FREQSAT in frequent itemset mining algorithms and privacy in data mining.