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Knowledge discovery interestingness measures based on unexpectedness

https://doi.org/10.1002/widm.1063
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What this work says

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

inferredcites →https://doi.org/10.1002/047174882xopenalex-snapshot
Elements of Information Theory
inferredcites →https://doi.org/10.1002/sam.10042openalex-snapshot
Randomization methods for assessing data analysis results on real‐valued matrices
inferredcites →https://doi.org/10.1007/3-540-44794-6_12openalex-snapshot
Interesting Fuzzy Association Rules in Quantitative Databases
inferredcites →https://doi.org/10.1007/3-540-48912-6_52openalex-snapshot
Visually Aided Exploration of Interesting Association Rules
inferredcites →https://doi.org/10.1007/3-540-64383-4_7openalex-snapshot
Interestingness of discovered association rules in terms of neighborhood-based unexpectedness
inferredcites →https://doi.org/10.1007/978-3-540-30214-8_22openalex-snapshot
Tiling Databases
inferredcites →https://doi.org/10.1007/978-3-540-44918-8openalex-snapshot
Quality Measures in Data Mining
inferredcites →https://doi.org/10.1007/978-3-540-70720-2_22openalex-snapshot
Mining Unexpected Web Usage Behaviors
inferredcites →https://doi.org/10.1007/978-3-642-34156-4_16openalex-snapshot
Formalizing Complex Prior Information to Quantify Subjective Interestingness of Frequent Pattern Sets
inferredcites →https://doi.org/10.1007/bfb0053707openalex-snapshot
Discovering unexpected patterns in temporal data using temporal logic
inferredcites →https://doi.org/10.1007/bfb0094799openalex-snapshot
On objective measures of rule surprisingness
inferredcites →https://doi.org/10.1007/s10618-010-0188-4openalex-snapshot
Using background knowledge to rank itemsets
inferredcites →https://doi.org/10.1007/s10618-010-0209-3openalex-snapshot
Maximum entropy models and subjective interestingness: an application to tiles in binary databases
inferredcites →https://doi.org/10.1007/s10994-013-5333-zopenalex-snapshot
Subjectively interesting alternative clusterings
inferredcites →https://doi.org/10.1016/s0950-7051(99)00019-2openalex-snapshot
On rule interestingness measures
inferredcites →https://doi.org/10.1017/s0269888905000408openalex-snapshot
A survey of interestingness measures for knowledge discovery
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/10.1038/sj.jors.2600425openalex-snapshot
Nonlinear Programming
inferredcites →https://doi.org/10.1073/pnas.0601602103openalex-snapshot
Modularity and community structure in networks
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/icdm.2010.20openalex-snapshot
Assessing Data Mining Results on Matrices with Randomization
inferredcites →https://doi.org/10.1109/icdm.2011.82openalex-snapshot
Interesting Multi-relational Patterns
inferredcites →https://doi.org/10.1109/icdm.2011.98openalex-snapshot
Maximum Entropy Modelling for Assessing Results on Real-Valued Data
inferredcites →https://doi.org/10.1109/proc.1982.12425openalex-snapshot
On the rationale of maximum-entropy methods
inferredcites →https://doi.org/10.1109/tkde.2010.29openalex-snapshot
Knowledge-Based Interactive Postmining of Association Rules Using Ontologies
inferredcites →https://doi.org/10.1137/1.9781611971255openalex-snapshot
Nonlinear Programming
inferredcites →https://doi.org/10.1137/1.9781611972801.14openalex-snapshot
An information-theoretic approach to finding informative noisy tiles in binary databases
inferredcites →https://doi.org/10.1145/1014052.1014074openalex-snapshot
Interestingness of frequent itemsets using Bayesian networks as background knowledge
inferredcites →https://doi.org/10.1145/1081870.1081887openalex-snapshot
Fast discovery of unexpected patterns in data, relative to a Bayesian network
inferredcites →https://doi.org/10.1145/1132960.1132963openalex-snapshot
Interestingness measures for data mining
inferredcites →https://doi.org/10.1145/1150402.1150502openalex-snapshot
Discovering interesting patterns through user's interactive feedback
inferredcites →https://doi.org/10.1145/1297332.1297338openalex-snapshot
Assessing data mining results via swap randomization
inferredcites →https://doi.org/10.1145/1557019.1557065openalex-snapshot
Tell me something I don't know
inferredcites →https://doi.org/10.1145/1871437.1871669openalex-snapshot
Finding unusual review patterns using unexpected rules
inferredcites →https://doi.org/10.1145/191246.191314openalex-snapshot
Finding interesting rules from large sets of discovered association rules
inferredcites →https://doi.org/10.1145/1964897.1964920openalex-snapshot
A framework for mining interesting pattern sets
inferredcites →https://doi.org/10.1145/2020408.2020497openalex-snapshot
An information theoretic framework for data mining
inferredcites →https://doi.org/10.1145/2559952openalex-snapshot
On Unexpectedness in Recommender Systems
inferredcites →https://doi.org/10.1145/312129.312272openalex-snapshot
Interestingness via what is not interesting
inferredcites →https://doi.org/10.1145/335191.335372openalex-snapshot
Mining frequent patterns without candidate generation
inferredcites →https://doi.org/10.1145/342009.335372openalex-snapshot
Mining frequent patterns without candidate generation
inferredcites →https://doi.org/10.1145/347090.347103openalex-snapshot
Small is beautiful
inferredcites →https://doi.org/10.1145/775047.775053openalex-snapshot
Selecting the right interestingness measure for association patterns
inferredcites →https://doi.org/10.1145/956750.956780openalex-snapshot
Mining unexpected rules by pushing user dynamics
inferredcites →https://doi.org/10.4018/978-1-60566-404-0.ch004openalex-snapshot
Semantics-Based Classification of Rule Interestingness Measures
inferredcites →https://doi.org/10.48550/arxiv.2006.09467openalex-snapshot
Tell Me Something I Don't Know: Randomization Strategies for Iterative Data Mining

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-030-44584-3_7openalex-snapshot
Gibbs Sampling Subjectively Interesting Tiles
inferred← citeshttps://doi.org/10.1007/978-3-319-93940-7_15openalex-snapshot
Subjective Interestingness in Association Rule Mining: A Theoretical Analysis
inferred← citeshttps://doi.org/10.1007/978-3-642-40994-3_39openalex-snapshot
A Theoretical Framework for Exploratory Data Mining: Recent Insights and Challenges Ahead
inferred← citeshttps://doi.org/10.1007/978-3-642-41398-8_3openalex-snapshot
Subjective Interestingness in Exploratory Data Mining
inferred← citeshttps://doi.org/10.1007/978-3-662-43968-5_9openalex-snapshot
Interactive Data Exploration Using Pattern Mining
inferred← citeshttps://doi.org/10.1007/s00500-015-1735-0openalex-snapshot
Mining unexpected patterns using decision trees and interestingness measures: a case study of endometriosis
inferred← citeshttps://doi.org/10.1007/s10618-013-0319-9openalex-snapshot
Interesting pattern mining in multi-relational data
inferred← citeshttps://doi.org/10.1007/s10618-020-00691-yopenalex-snapshot
Large-scale network motif analysis using compression
inferred← citeshttps://doi.org/10.1007/s10994-013-5333-zopenalex-snapshot
Subjectively interesting alternative clusterings
inferred← citeshttps://doi.org/10.1007/s10994-015-5539-3openalex-snapshot
Subjective interestingness of subgraph patterns
inferred← citeshttps://doi.org/10.1007/s41060-016-0004-3openalex-snapshot
P-N-RMiner: a generic framework for mining interesting structured relational patterns
inferred← citeshttps://doi.org/10.1016/j.datak.2024.102393openalex-snapshot
Coupling MDL and Markov chain Monte Carlo to sample diverse pattern sets
inferred← citeshttps://doi.org/10.1016/j.procs.2014.08.107openalex-snapshot
Pruning Statistically Insignificant Association Rules in the Presence of High-confidence Rules in Web Usage Data
inferred← citeshttps://doi.org/10.1109/aims.2013.26openalex-snapshot
Mining Unexpected Patterns by Decision Trees with Interestingness Measures
inferred← citeshttps://doi.org/10.1109/dsaa.2015.7344837openalex-snapshot
P-N-RMiner: A generic framework for mining interesting structured relational patterns
inferred← citeshttps://doi.org/10.1109/ictai.2013.85openalex-snapshot
Active Preference Learning for Ranking Patterns
inferred← citeshttps://doi.org/10.1109/wiiat50758.2020.00024openalex-snapshot
Mining RDF Data of COVID-19 Scientific Literature for Interesting Association Rules
inferred← citeshttps://doi.org/10.1145/2559952openalex-snapshot
On Unexpectedness in Recommender Systems
inferred← citeshttps://doi.org/10.1145/3772318.3790989openalex-snapshot
Creativity from Surprise: Bridging the Gap Between Fashion Designers' Inspiration Work and AI Creative Support Tools
inferred← citeshttps://doi.org/10.1587/transinf.2019iip0008openalex-snapshot
Characterization of Interestingness Measures Using Correlation Analysis and Association Rule Mining
inferred← citeshttps://doi.org/10.1609/aaai.v31i1.10687openalex-snapshot
The Unusual Suspects: Deep Learning Based Mining of Interesting Entity Trivia from Knowledge Graphs
inferred← citeshttps://doi.org/10.18297/etd/2693openalex-snapshot
Peeking into the other half of the glass : handling polarization in recommender systems.
inferred← citeshttps://doi.org/10.3844/ajassp.2013.1160.1165openalex-snapshot
A REVIEW ON DATA MINING IN BANKING SECTOR
inferred← citeshttps://doi.org/10.4018/978-1-5225-3725-0.ch008openalex-snapshot
Advanced Issues of Knowledge Management, Knowledge Discovery, and Organizational Communication
inferred← citeshttps://doi.org/10.48550/arxiv.1905.01546openalex-snapshot
Latent Unexpected and Useful Recommendation
inferred← citeshttps://doi.org/10.5121/ijaia.2013.4201openalex-snapshot
Probabilistic Measures for Interestingness of Deviations - A Survey
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