Mining Non-Redundant Association Rules

Authors:
Mohammed J. Zaki
Affiliations:
Computer Science Department, Rensselaer Polytechnic Institute, Troy NY 12180, USA. zaki@cs.rpi.edu
Venue:
Data Mining and Knowledge Discovery
Year:
2004

Citing 14
Cited 94

Finding interesting rules from large sets of discovered association rules

CIKM '94 Proceedings of the third international conference on Information and knowledge management
Dynamic itemset counting and implication rules for market basket data

SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Fast discovery of association rules

Advances in knowledge discovery and data mining
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
Efficient mining of association rules using closed itemset lattices

Information Systems
Pruning and summarizing the discovered associations

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the most interesting rules

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns with counting inference

ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Formal Concept Analysis: Mathematical Foundations

Formal Concept Analysis: Mathematical Foundations
Pincer Search: A New Algorithm for Discovering the Maximum Frequent Set

EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases

Proceedings of the 17th International Conference on Data Engineering
An Efficient Algorithm for Mining Association Rules in Large Databases

VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Bases for Association Rules Using Closed Sets

ICDE '00 Proceedings of the 16th International Conference on Data Engineering

Mining risk patterns in medical data

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
Using Information-Theoretic Measures to Assess Association Rule Interestingness

ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
On Optimal Rule Discovery

IEEE Transactions on Knowledge and Data Engineering
Association mining

ACM Computing Surveys (CSUR)
Discovering significant rules

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Horn axiomatizations for sequential data

Theoretical Computer Science
BitTableFI: An efficient mining frequent itemsets algorithm

Knowledge-Based Systems
Fast factorization by similarity in formal concept analysis of data with fuzzy attributes

Journal of Computer and System Sciences
Discovering debtor patterns of centrelink customers

AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
Comprehending implementation recipes of framework-provided concepts through dynamic analysis

Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion
Webview selection from user access patterns

Proceedings of the ACM first Ph.D. workshop in CIKM
Generating concise association rules

Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A Galois Lattice framework to handle updates in the mining of closed itemsets in dynamic databases

COMPUTE '08 Proceedings of the 1st Bangalore Annual Compute Conference
Redundant association rules reduction techniques

International Journal of Business Intelligence and Data Mining
A method for mining quantitative association rules

SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns

Machine Learning
Closed Sets for Labeled Data

The Journal of Machine Learning Research
Lindig's Algorithm for Concept Lattices over Graded Attributes

MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Trees in Concept Lattices

MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
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
Deriving non-redundant approximate association rules from hierarchical datasets

Proceedings of the 17th ACM conference on Information and knowledge management
Deduction Schemes for Association Rules

DS '08 Proceedings of the 11th International Conference on Discovery Science
Post-processing of associative classification rules using closed sets

Expert Systems with Applications: An International Journal
Efficient discovery of risk patterns in medical data

Artificial Intelligence in Medicine
Non-redundant sequential rules-Theory and algorithm

Information Systems
A Novel Classification Algorithm Based on Association Rules Mining

Knowledge Acquisition: Approaches, Algorithms and Applications
Granule Oriented Data Warehouse Model

RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
A new generic basis of "factual" and "implicative" association rules

Intelligent Data Analysis
Redescription mining: structure theory and algorithms

AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
On mining closed sets in multi-relational data

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Discovering hybrid temporal patterns from sequences consisting of point- and interval-based events

Data & Knowledge Engineering
Self-sufficient itemsets: An approach to screening potentially interesting associations between items

ACM Transactions on Knowledge Discovery from Data (TKDD)
Mining multidimensional and multilevel sequential patterns

ACM Transactions on Knowledge Discovery from Data (TKDD)
An Algorithm of Mining Class Association Rules

ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Discovering the Structures of Open Source Programs from Their Developer Mailing Lists

DS '09 Proceedings of the 12th International Conference on Discovery Science
Comparison of Data Structures for Computing Formal Concepts

MDAI '09 Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence
Frequent closed multi-dimensional multi-level pattern mining

ACST '08 Proceedings of the Fourth IASTED International Conference on Advances in Computer Science and Technology
Strategy for mining association rules for web pages based on formal concept analysis

Applied Soft Computing
A parameterized algorithm for exploring concept lattices

ICFCA'07 Proceedings of the 5th international conference on Formal concept analysis
About the lossless reduction of the minimal generator family of a context

ICFCA'07 Proceedings of the 5th international conference on Formal concept analysis
Background knowledge in formal concept analysis: constraints via closure operators

Proceedings of the 2010 ACM Symposium on Applied Computing
Succinct system of minimal generators: a thorough study, limitations and new definitions

CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
Generic association rule bases: are they so succinct?

CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
Granule mining oriented data warehousing model for representations of multidimensional association rules

International Journal of Intelligent Information and Database Systems
Margin-closed frequent sequential pattern mining

Proceedings of the ACM SIGKDD Workshop on Useful Patterns
Frequent regular itemset mining

Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A fast pruning redundant rule method using Galois connection

Applied Soft Computing
Two measures of objective novelty in association rule mining

PAKDD'09 Proceedings of the 13th Pacific-Asia international conference on Knowledge discovery and data mining: new frontiers in applied data mining
Clinical informatics to diagnose cardiac diseases based on data mining

ITBAM'10 Proceedings of the First international conference on Information technology in bio- and medical informatics
Mining monolingual and bilingual corpora

Intelligent Data Analysis
Mining informative rule set for prediction over a sliding window

ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Mining minimal non-redundant association rules using frequent itemsets lattice

International Journal of Intelligent Systems Technologies and Applications
Building a highly-compact and accurate associative classifier

Applied Intelligence
Reliable representations for association rules

Data & Knowledge Engineering
Finding association rules in semantic web data

Knowledge-Based Systems
Efficient reduction of the number of associations rules using fuzzy clustering on the data

ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
Extracting compact and information lossless sets of fuzzy association rules

Fuzzy Sets and Systems
Mining classification rules without support: an anti-monotone property of Jaccard measure

DS'11 Proceedings of the 14th international conference on Discovery science
Fast algorithm for computing fixpoints of Galois connections induced by object-attribute relational data

Information Sciences: an International Journal
Closed sets for labeled data

PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Redundant association rules reduction techniques

AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
On a mathematical relationship between the fixed point and the closed itemset in association rule mining

AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
EGEA: a new hybrid approach towards extracting reduced generic association rule set (application to AML blood cancer therapy)

DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
An efficiently algorithm based on itemsets-lattice and bitmap index for finding frequent itemsets

FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Employing inductive databases in concrete applications

Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
About the end-user for discovering knowledge

ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets

Expert Systems with Applications: An International Journal
Formal concept analysis with constraints by closure operators

ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
Structures of association rule set

ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
Mining of multiobjective non-redundant association rules in data streams

ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
ACE: exploiting correlation for energy-efficient and continuous context sensing

Proceedings of the 10th international conference on Mobile systems, applications, and services
Cluster_KDD: a visual clustering and knowledge discovery platform based on concept lattice

ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Computing Formal Concepts by Attribute Sorting

Fundamenta Informaticae - Concept Lattices and Their Applications
Optimonotone Measures For Optimal Rule Discovery

Computational Intelligence
Incomplete decision contexts: Approximate concept construction, rule acquisition and knowledge reduction

International Journal of Approximate Reasoning
A new method for mining Frequent Weighted Itemsets based on WIT-trees

Expert Systems with Applications: An International Journal
Mining frequent itemsets with dualistic constraints

PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Proxemic conceptual network based on ontology enrichment for representing documents in IR

EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
Tractable reasoning problems with fully-characterized association rules

ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
Two scalable algorithms for associative text classification

Information Processing and Management: an International Journal
Closed and noise-tolerant patterns in n-ary relations

Data Mining and Knowledge Discovery
Dimensions as Virtual Items: Improving the predictive ability of top-N recommender systems

Information Processing and Management: an International Journal
A lattice-based approach for mining most generalization association rules

Knowledge-Based Systems
Closure-based constraints in formal concept analysis

Discrete Applied Mathematics
Formal and computational properties of the confidence boost of association rules

ACM Transactions on Knowledge Discovery from Data (TKDD)
An efficient method for mining frequent itemsets with double constraints

Engineering Applications of Artificial Intelligence
A prediction framework based on contextual data to support Mobile Personalized Marketing

Decision Support Systems
An efficient approach for mining cross-level closed itemsets and minimal association rules using closed itemset lattices

Expert Systems with Applications: An International Journal
Granularity of attributes in formal concept analysis

Information Sciences: an International Journal
Mining closed patterns in relational, graph and network data

Annals of Mathematics and Artificial Intelligence
Key roles of closed sets and minimal generators in concise representations of frequent patterns

Intelligent Data Analysis
Discovering descriptive rules in relational dynamic graphs

Intelligent Data Analysis - Dynamic Networks and Knowledge Discovery
Derivation digraphs for dependencies in ordinal and similarity-based data

Information Sciences: an International Journal

Quantified Score

Hi-index	0.01

Visualization

Abstract

The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for associations based on the concept of closed frequent itemsets. The number of non-redundant rules produced by the new approach is exponentially (in the length of the longest frequent itemset) smaller than the rule set from the traditional approach. Experiments using several “hard” as well as “easy” real and synthetic databases confirm the utility of our framework in terms of reduction in the number of rules presented to the user, and in terms of time.