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Interestingness of association rules in data mining: Issues relevant to e-commerce

https://doi.org/10.1007/bf02706249
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What this work says

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

inferredcites →https://doi.org/10.1002/9780470316801openalex-snapshot
Finding Groups in Data
inferredcites →https://doi.org/10.1002/net.1975.5.3.299openalex-snapshot
GRAPH THEORY WITH APPLICATIONS TO ENGINEERING AND COMPUTER SCIENCE
inferredcites →https://doi.org/10.1007/3-540-45571-x_11openalex-snapshot
Exception Rule Mining with a Relative Interestingness Measure
inferredcites →https://doi.org/10.1007/978-3-540-39663-5_9openalex-snapshot
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
inferredcites →https://doi.org/10.1007/bf00962821openalex-snapshot
Selecting among rules induced from a hurricane database
inferredcites →https://doi.org/10.1007/bfb0094799openalex-snapshot
On objective measures of rule surprisingness
inferredcites →https://doi.org/10.1016/c2013-0-06161-0openalex-snapshot
Cluster Analysis for Applications
inferredcites →https://doi.org/10.1016/s0167-739x(97)00019-8openalex-snapshot
Mining generalized association rules
inferredcites →https://doi.org/10.1016/s0167-9236(99)00053-6openalex-snapshot
Unexpectedness as a measure of interestingness in knowledge discovery
inferredcites →https://doi.org/10.1016/s0306-4379(03)00072-3openalex-snapshot
Selecting the right objective measure for association analysis
inferredcites →https://doi.org/10.1016/s0898-1221(96)90007-3openalex-snapshot
Advances in knowledge discovery and data mining
inferredcites →https://doi.org/10.1016/s0950-7051(02)00050-3openalex-snapshot
Knowledge-based association rule mining using AND–OR taxonomies
inferredcites →https://doi.org/10.1016/s0950-7051(99)00019-2openalex-snapshot
On rule interestingness measures
inferredcites →https://doi.org/10.1016/s0969-6989(02)00062-0openalex-snapshot
E-commerce and the retail process: a review
inferredcites →https://doi.org/10.1023/a:1009804230409openalex-snapshot
E-Commerce Recommendation Applications
inferredcites →https://doi.org/10.1023/a:1009839827683openalex-snapshot
Expert-Driven Validation of Rule-Based User Models in Personalization Applications
inferredcites →https://doi.org/10.1023/a:1009840925866openalex-snapshot
Applications of Data Mining to Electronic Commerce
inferredcites →https://doi.org/10.1023/a:1009843912662openalex-snapshot
Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising
inferredcites →https://doi.org/10.1023/a:1009895914772openalex-snapshot
Constraint-Based Rule Mining in Large, Dense Databases
inferredcites →https://doi.org/10.1023/a:1016308404627openalex-snapshot
Techniques of Cluster Algorithms in Data Mining
inferredcites →https://doi.org/10.1023/b:fodm.0000022043.43885.55openalex-snapshot
A Framework for Evaluating Knowledge-Based Interestingness of Association Rules
inferredcites →https://doi.org/10.1109/69.553165openalex-snapshot
What makes patterns interesting in knowledge discovery systems
inferredcites →https://doi.org/10.1109/69.824588openalex-snapshot
Finding interesting patterns using user expectations
inferredcites →https://doi.org/10.1109/69.971183openalex-snapshot
Mining associations with the collective strength approach
inferredcites →https://doi.org/10.1109/icde.1998.655804openalex-snapshot
Cyclic association rules
inferredcites →https://doi.org/10.1109/icde.1998.655812openalex-snapshot
Mining for strong negative associations in a large database of customer transactions
inferredcites →https://doi.org/10.1109/icdm.2001.989497openalex-snapshot
Integrating e-commerce and data mining: architecture and challenges
inferredcites →https://doi.org/10.1109/icdm.2002.1183986openalex-snapshot
On the mining of substitution rules for statistically dependent items
inferredcites →https://doi.org/10.1109/icdm.2002.1184007openalex-snapshot
Generating an informative cover for association rules
inferredcites →https://doi.org/10.1109/icdm.2002.1184027openalex-snapshot
Exploring interestingness through clustering: a framework
inferredcites →https://doi.org/10.1109/icdm.2004.10107openalex-snapshot
A Transaction-Based Neighbourhood-Driven Approach to Quantifying Interestingness of Association Rules
inferredcites →https://doi.org/10.1109/proc.1975.9996openalex-snapshot
Graph theory with applications to engineering and computer science
inferredcites →https://doi.org/10.1137/1.9781611972740.17openalex-snapshot
Hierarchical Clustering for thematic browsing and summarization of large sets of Association Rules
inferredcites →https://doi.org/10.1145/170035.170072openalex-snapshot
Mining association rules between sets of items in large databases
inferredcites →https://doi.org/10.1145/191246.191314openalex-snapshot
Finding interesting rules from large sets of discovered association rules
inferredcites →https://doi.org/10.1145/245108.245121openalex-snapshot
Recommender systems
inferredcites →https://doi.org/10.1145/253260.253325openalex-snapshot
Dynamic itemset counting and implication rules for market basket data
inferredcites →https://doi.org/10.1145/253260.253327openalex-snapshot
Beyond market baskets
inferredcites →https://doi.org/10.1145/312129.312272openalex-snapshot
Interestingness via what is not interesting
inferredcites →https://doi.org/10.1145/331499.331504openalex-snapshot
Data clustering
inferredcites →https://doi.org/10.1145/347090.347101openalex-snapshot
Generating non-redundant association rules
inferredcites →https://doi.org/10.1145/347090.347128openalex-snapshot
Multi-level organization and summarization of the discovered rules
inferredcites →https://doi.org/10.1145/352871.352887openalex-snapshot
Analysis of recommendation algorithms for e-commerce
inferredcites →https://doi.org/10.1145/358108.358114openalex-snapshot
Beyond intratransaction association analysis
inferredcites →https://doi.org/10.1145/363951.363956openalex-snapshot
Theory of dependence values
inferredcites →https://doi.org/10.1145/380995.381018openalex-snapshot
Measuring lift quality in database marketing
inferredcites →https://doi.org/10.1145/507533.507535openalex-snapshot
What's interesting about Cricket?
inferredcites →https://doi.org/10.1145/545151.545174openalex-snapshot
Evolving data into mining solutions for insights
inferredcites →https://doi.org/10.1145/775047.775053openalex-snapshot
Selecting the right interestingness measure for association patterns
inferredcites →https://doi.org/10.1145/775047.775126openalex-snapshot
SimRank
inferredcites →https://doi.org/10.1184/r1/6608795openalex-snapshot
Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining
inferredcites →https://doi.org/10.1287/mnsc.49.10.1275.17311openalex-snapshot
E-Business and Management Science: Mutual Impacts (Part 1 of 2)
inferredcites →https://doi.org/10.1287/mnsc.49.10.1344.17313openalex-snapshot
The Role of the Management Sciences in Research on Personalization
inferredcites →https://doi.org/10.1287/mnsc.49.11.1445.20579openalex-snapshot
E-Business and Management Science: Mutual Impacts (Part 2 of 2)
inferredcites →https://doi.org/10.1887/0750303123/b365c43openalex-snapshot
Classification and regression
inferredcites →https://doi.org/10.2307/2288003openalex-snapshot
Classification and Regression Trees.
inferredcites →https://doi.org/10.2307/2530946openalex-snapshot
Classification and Regression Trees.
inferredcites →https://doi.org/10.5860/choice.28-4558openalex-snapshot
Finding groups in data: an introduction to cluster analysis

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9781118617151.ch35openalex-snapshot
Galois Closure Based Association Rule Mining From Biological Data
inferred← citeshttps://doi.org/10.1002/widm.18openalex-snapshot
On the discovery of association rules by means of evolutionary algorithms
inferred← citeshttps://doi.org/10.1007/978-3-642-29958-2_5openalex-snapshot
PAR-COM: A New Methodology for Post-processing Association Rules
inferred← citeshttps://doi.org/10.1007/978-3-642-45111-9_26openalex-snapshot
Subjective Evaluation of Labeling Methods for Association Rule Clustering
inferred← citeshttps://doi.org/10.1007/b137171_37openalex-snapshot
Analysis of Academic Results for Informatics Course Improvement Using Association Rule Mining
inferred← citeshttps://doi.org/10.1063/5.0228165openalex-snapshot
Association rule mining of household expenditure survey in Malaysia by using Apriori algorithm
inferred← citeshttps://doi.org/10.1109/fskd.2015.7382015openalex-snapshot
A new validation method of fuzzy association rules based on the Structural Equation Modeling
inferred← citeshttps://doi.org/10.1109/icetet.2010.98openalex-snapshot
Conceptual Mapping of Risk Management to Data Mining
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Support Vector Machine Classification of Probability Models and Peptide Features for Improved Peptide Identification from Shotgun Proteomics
inferred← citeshttps://doi.org/10.1109/icmla.2007.45openalex-snapshot
An Itemset-Driven Cluster-Oriented Approach to Extract Compact and Meaningful Sets of Association Rules
inferred← citeshttps://doi.org/10.1109/icmtma52658.2021.00117openalex-snapshot
Research on E-commerce Data Mining and Managing Model in The Process of Farmers' Welfare Growth
inferred← citeshttps://doi.org/10.1145/1363686.1363967openalex-snapshot
Including the user in the knowledge discovery loop
inferred← citeshttps://doi.org/10.11606/t.55.2007.tde-10122007-160534openalex-snapshot
Generalização de regras de associação utilizando conhecimento de domínio e avaliação do conhecimento generalizado
inferred← citeshttps://doi.org/10.1504/ijdats.2012.045124openalex-snapshot
Normalised support: a virtual angle of measurement of 'interestingness'
inferred← citeshttps://doi.org/10.15611/ie.2017.1.06openalex-snapshot
EVALUATION OF THE ON-LINE COMMERCIAL SERVICE QUALITY BASED ON ASSOCIATION RULES
inferred← citeshttps://doi.org/10.17485/ijst/2015/v8i15/76693openalex-snapshot
Analysing the Quality of Association Rules by Computing an Interestingness Measures
inferred← citeshttps://doi.org/10.3390/ijerph20043332openalex-snapshot
Immersive Experience and Climate Change Monitoring in Digital Landscapes: Evidence from Somatosensory Sense and Comfort
inferred← citeshttps://doi.org/10.4018/978-1-5225-0613-3.ch001openalex-snapshot
Mastering Web Mining and Information Retrieval in the Digital Age
inferred← citeshttps://doi.org/10.4018/jdwm.2013010101openalex-snapshot
A Survey on Fuzzy Association Rule Mining
inferred← citeshttps://doi.org/10.4067/s0718-18762014000100001openalex-snapshot
Editorial: Data Mining in Electronic Commerce - Support vs. Confidence
inferred← citeshttps://doi.org/10.48550/arxiv.1312.4800openalex-snapshot
New Approach to Optimize the Time of Association Rules Extraction
inferred← citeshttps://doi.org/10.5121/csit.2018.80600openalex-snapshot
Computer Science & Information Technology
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Validation Method of Fuzzy Association Rules Based on Fuzzy Formal Concept Analysis and Structural Equation Model
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