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Representative association rules and minimum condition maximum consequence association rules

https://doi.org/10.1007/bfb0094839
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-64383-4openalex-snapshot
Research and development in knowledge discovery and data mining : Second Pacific-Asia Conference, PAKDD-98, Melbourne, Australia, April 15-17, 1998 : proceedings
inferredcites →https://doi.org/10.1007/3-540-64383-4_17openalex-snapshot
Representative association rules
inferredcites →https://doi.org/10.1007/3-540-64383-4_50openalex-snapshot
Mining association rules for estimation and prediction
inferredcites →https://doi.org/10.1007/3-540-69115-4_30openalex-snapshot
Fast Discovery of Representative Association Rules
inferredcites →https://doi.org/10.1007/978-3-540-88425-5openalex-snapshot
Rough Sets and Current Trends in Computing
inferredcites →https://doi.org/10.1016/s0167-739x(97)00019-8openalex-snapshot
Mining generalized association rules
inferredcites →https://doi.org/10.1016/s0898-1221(96)90007-3openalex-snapshot
Advances in knowledge discovery and data mining
inferredcites →https://doi.org/10.1145/170035.170072openalex-snapshot
Mining association rules between sets of items in large databases
inferredcites →https://doi.org/10.5555/140629.140633openalex-snapshot
Knowledge discovery in databases

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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An efficient class association rule‐pruning method for unified intrusion detection system using genetic algorithm
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EGEA : A New Hybrid Approach Towards Extracting Reduced Generic Association Rule Set (Application to AML Blood Cancer Therapy)
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GARC: A New Associative Classification Approach
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Datascape Survey Using the Cascade Model
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Legitimate Approach to Association Rules under Incompleteness
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Closed Set Based Discovery of Representative Association Rules
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Direct and Incremental Computing of Maximal Covering Rules
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Quantitative Redundancy in Partial Implications
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Enumerating Non-redundant Association Rules Using Satisfiability
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Generating Representative from Clusters of Association Rules on Numeric Attributes
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A Distance-Based Clustering and Selection of Association Rules on Numeric Attributes
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Generic Association Rule Bases: Are They so Succinct?
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Minimum-Size Bases of Association Rules
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Deduction Schemes for Association Rules
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Mining Top-K Non-redundant Association Rules
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Discovering Interesting Rules from Financial Data
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Discovering Interesting Rules From Dense Data
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Performance Comparisons in Association Rule Mining Over Public Datasets
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PISRuleGrowth: mining periodic intra-sequential rules common to multiple sequences
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Effective elimination of redundant association rules
inferred← citeshttps://doi.org/10.1016/j.eswa.2008.08.046openalex-snapshot
Post-processing of associative classification rules using closed sets
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Formal Concept Analysis in knowledge processing: A survey on models and techniques
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Extracting compact and information lossless sets of fuzzy association rules
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An efficient method for pruning redundant negative and positive association rules
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Data-driven adaptive selection of rule quality measures for improving rule induction and filtration algorithms
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Enabling Far-Edge Analytics: Performance Profiling of Frequent Pattern Mining Algorithms
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Evaluating class association rules using Genetic Relation Programming
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Mining multi-class datasets using Genetic Relation Algorithm for rule reduction
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Mining Condensed and Lossless Association Rules by Pruning Redundancy
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Extracting compact and information lossless set of fuzzy association rules
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A New Method for Eliminating Redundant Association Rules
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Application of unsupervised machine learning to identify areas of blood product wastage in transfusion medicine
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Basic Association Rules
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SUCCINCT MINIMAL GENERATORS: THEORETICAL FOUNDATIONS AND APPLICATIONS
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TNS
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Formal and computational properties of the confidence boost of association rules
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Visualização como suporte à extração e exploração de regras de associação
inferred← citeshttps://doi.org/10.24963/ijcai.2020/176openalex-snapshot
On the Enumeration of Association Rules: A Decomposition-based Approach
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Efficient SAT-Based Encodings of Conditional Cardinality Constraints
inferred← citeshttps://doi.org/10.3233/faia200110openalex-snapshot
Exploiting Incomparability in Solution Dominance: Improving General Purpose Constraint-Based Mining
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Reducing redundancy in characteristic rule discovery by using integer programming techniques
inferred← citeshttps://doi.org/10.3233/jcm-2011-0374openalex-snapshot
Mining redundant industrial alarm occurrences with association rules extraction and complex networks modeling
inferred← citeshttps://doi.org/10.4018/978-1-60566-404-0.ch005openalex-snapshot
Post-Processing for Rule Reduction Using Closed Set
inferred← citeshttps://doi.org/10.4018/978-1-60566-404-0.ch013openalex-snapshot
Frequent Closed Itemsets Based Condensed Representations for Association Rules
inferred← citeshttps://doi.org/10.48550/arxiv.1504.03620openalex-snapshot
Quantitative Redundancy in Partial Implications
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Efficient Encodings of Conditional Cardinality Constraints
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Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining
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Contributions to the Formalization and Extraction of Generic Bases of Association Rules
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Mining Constant Conditional Functional Dependencies for Improving Data Quality
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A Hybrid Algorithm for Association Rule Hiding using Representative Rule
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Fouille de données par contraintes
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Fouille de données déclarative basée sur la programmation par contraintes.
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Efficient Pruning of Class Association Rules Using Statistics and Genetic Relation Algorithm
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