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
A condensed representation to find frequent patterns
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Concise Representation of Frequent Patterns Based on Disjunction-Free Generators
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Approximation of Frequency Queris by Means of Free-Sets
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Frequent Closures as a Concise Representation for Binary Data Mining
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Relational Association Rules: Getting WARMeR
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
Dataless Transitions Between Concise Representations of Frequent Patterns
Journal of Intelligent Information Systems
Zigzag: a new algorithm for mining large inclusion dependencies in databases
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Weighted Association Rule Mining using weighted support and significance framework
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining dependence rules by finding largest itemset support quota
Proceedings of the 2004 ACM symposium on Applied computing
Reducing borders of k-disjunction free representations of frequent patterns
Proceedings of the 2004 ACM symposium on Applied computing
Approximating a collection of frequent sets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Essential classification rule sets
ACM Transactions on Database Systems (TODS)
Computational complexity of itemset frequency satisfiability
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Summarizing itemset patterns: a profile-based approach
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Fast and Memory Efficient Mining of Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
Summarization — Compressing Data into an Informative Representation
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Blocking Anonymity Threats Raised by Frequent Itemset Mining
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
On Characterization and Discovery of Minimal Unexpected Patterns in Rule Discovery
IEEE Transactions on Knowledge and Data Engineering
ACM Computing Surveys (CSUR)
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
Towards low-perturbation anonymity preserving pattern discovery
Proceedings of the 2006 ACM symposium on Applied computing
Frequent closed itemset based algorithms: a thorough structural and analytical survey
ACM SIGKDD Explorations Newsletter
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting redundancy-aware top-k patterns
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing itemset patterns using probabilistic models
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
On compressing frequent patterns
Data & Knowledge Engineering
Data Mining and Knowledge Discovery
Discovering Significant Patterns
Machine Learning
Summarization – compressing data into an informative representation
Knowledge and Information Systems
The implication problem for measure-based constraints
Information Systems
Discovering shared conceptualizations in folksonomies
Web Semantics: Science, Services and Agents on the World Wide Web
Itemset frequency satisfiability: Complexity and axiomatization
Theoretical Computer Science
An efficient algorithm for mining closed inter-transaction itemsets
Data & Knowledge Engineering
Anonymity preserving pattern discovery
The VLDB Journal — The International Journal on Very Large Data Bases
A survey on algorithms for mining frequent itemsets over data streams
Knowledge and Information Systems
Adequate condensed representations of patterns
Data Mining and Knowledge Discovery
Mining conjunctive sequential patterns
Data Mining and Knowledge Discovery
MINI: Mining Informative Non-redundant Itemsets
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Minimum-Size Bases of Association Rules
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Decomposable Families of Itemsets
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
A new concise representation of frequent itemsets using generators and a positive border
Knowledge and Information Systems
Maximum entropy based significance of itemsets
Knowledge and Information Systems
Blind paraunitary equalization
Signal Processing
Mining non-derivable frequent itemsets over data stream
Data & Knowledge Engineering
Capturing truthiness: mining truth tables in binary datasets
Proceedings of the 2009 ACM symposium on Applied Computing
Non-redundant sequential rules-Theory and algorithm
Information Systems
Closures of Downward Closed Representations of Frequent Patterns
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
International Journal of Data Analysis Techniques and Strategies
Non-Derivable Item Set and Non-Derivable Literal Set Representations of Patterns Admitting Negation
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
A Condensed Representation of Itemsets for Analyzing Their Evolution over Time
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
ACM Transactions on Knowledge Discovery from Data (TKDD)
Mining multidimensional and multilevel sequential patterns
ACM Transactions on Knowledge Discovery from Data (TKDD)
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
About the lossless reduction of the minimal generator family of a context
ICFCA'07 Proceedings of the 5th international conference on Formal concept analysis
Discovering association rules in incomplete transactional databases
Transactions on rough sets VI
Integrating decision tree learning into inductive databases
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Frequent pattern mining and knowledge indexing based on zero-suppressed BDDs
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Mining correct properties in incomplete databases
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Summarising data by clustering items
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
ACM Transactions on Database Systems (TODS)
Krimp: mining itemsets that compress
Data Mining and Knowledge Discovery
Reliable representations for association rules
Data & Knowledge Engineering
Theoretical bounds on the size of condensed representations
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Database transposition for constrained (closed) pattern mining
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
An automata approach to pattern collections
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Implicit enumeration of patterns
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Condensed representation of EPs and patterns quantified by frequency-based measures
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Summarizing frequent patterns using profiles
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Essential patterns: a perfect cover of frequent patterns
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Efficient mining of association rules based on formal concept analysis
Formal Concept Analysis
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Boolean formulas and frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Mining succinct systems of minimal generators of formal concepts
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Transaction databases, frequent itemsets, and their condensed representations
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
A false negative maximal frequent itemset mining algorithm over stream
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Finding minimum representative pattern sets
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
On nested palindromes in clickstream data
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
Mining succinct and high-coverage API usage patterns from source code
Proceedings of the 10th Working Conference on Mining Software Repositories
Summarizing probabilistic frequent patterns: a fast approach
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Anytime algorithms for mining groups with maximum coverage
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Misleading Generalized Itemset discovery
Expert Systems with Applications: An International Journal
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
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Recent studies on frequent itemset mining algorithms resulted in significant performance improvements. However, if the minimal support threshold is set too low, or the data is highly correlated, the number of frequent itemsets itself can be prohibitively large. To overcome this problem, recently several proposals have been made to construct a concise representation of the frequent itemsets, instead of mining all frequent itemsets. The main goal of this paper is to identify redundancies in the set of all frequent itemsets and to exploit these redundancies in order to reduce the result of a mining operation. We present deduction rules to derive tight bounds on the support of candidate itemsets. We show how the deduction rules allow for constructing a minimal representation for all frequent itemsets. We also present connections between our proposal and recent proposals for concise representations and we give the results of experiments on real-life datasets that show the effectiveness of the deduction rules. In fact, the experiments even show that in many cases, first mining the concise representation, and then creating the frequent itemsets from this representation outperforms existing frequent set mining algorithms.