On the public citation graph

Learning from inconsistent and noisy data: The AQ18 approach

0 signed · 57 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1007/978-3-642-48397-4_8openalex-snapshot
An Artificial Intelligence Approach
inferredcites →https://doi.org/10.1007/978-3-662-12405-5openalex-snapshot
Machine Learning
inferredcites →https://doi.org/10.1007/bf00116251openalex-snapshot
Induction of Decision Trees
inferredcites →https://doi.org/10.1007/bf00116835openalex-snapshot
The CN2 Induction Algorithm
inferredcites →https://doi.org/10.1016/0004-3702(83)90016-4openalex-snapshot
A theory and methodology of inductive learning
inferredcites →https://doi.org/10.1016/b978-1-55860-335-6.50017-9openalex-snapshot
Incremental Reduced Error Pruning
inferredcites →https://doi.org/10.1016/b978-1-55860-377-6.50023-2openalex-snapshot
Fast Effective Rule Induction
inferredcites →https://doi.org/10.1023/a:1022682318197openalex-snapshot
Learning Two-Tiered Descriptions of Flexible Concepts: The POSEIDON System
inferredcites →https://doi.org/10.1023/a:1022687019898openalex-snapshot
Editorial: On Machine Learning
inferredcites →https://doi.org/10.13021/mars/3550openalex-snapshot
Learning in an Inconsistent World: Rule Selection in AQ18
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.

inferred← citeshttps://doi.org/10.1002/widm.1124openalex-snapshot
Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1007/3-540-32392-9_2openalex-snapshot
Rule Induction for Click-Stream Analysis: Set Covering and Compositional Approach
inferred← citeshttps://doi.org/10.1007/3-540-44673-7_2openalex-snapshot
Learning Patterns in Noisy Data: The AQ Approach
inferred← citeshttps://doi.org/10.1007/3-540-45571-x_2openalex-snapshot
Inductive Databases and Knowledge Scouts
inferred← citeshttps://doi.org/10.1007/978-3-030-33509-0_63openalex-snapshot
Distributed Task Placement in the Fog: A Positioning Paper
inferred← citeshttps://doi.org/10.1007/978-3-319-18781-5_3openalex-snapshot
ADX Algorithm for Supervised Classification
inferred← citeshttps://doi.org/10.1007/978-3-540-36562-4_28openalex-snapshot
The Development of the Inductive Database System VINLEN: A Review of Current Research
inferred← citeshttps://doi.org/10.1007/978-3-540-39985-8_3openalex-snapshot
ADX Algorithm: a brief description of a rule based classifier
inferred← citeshttps://doi.org/10.1007/978-3-540-73847-3_13openalex-snapshot
Extension of the Top-Down Data-Driven Strategy to ILP
inferred← citeshttps://doi.org/10.1007/978-3-642-01129-0_79openalex-snapshot
Evolutionary Optimization Guided by Entropy-Based Discretization
inferred← citeshttps://doi.org/10.1007/978-3-642-02541-9openalex-snapshot
Automating the Design of Data Mining Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-642-02541-9_3openalex-snapshot
Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-642-15251-1_38openalex-snapshot
A Discretization Algorithm for Uncertain Data
inferred← citeshttps://doi.org/10.1007/978-3-7908-1803-1_10openalex-snapshot
Hybrid Inductive Machine Learning: An Overview of CLIP Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-7908-1834-5_45openalex-snapshot
A Knowledge Scout for Discovering Medical Patterns: Methodology and System SCAMP
inferred← citeshttps://doi.org/10.1007/bfb0098209openalex-snapshot
Learning efficient rulesets from fuzzy data with a genetic algorithm
inferred← citeshttps://doi.org/10.1007/s10479-023-05715-6openalex-snapshot
A multi-criteria approach to evolve sparse neural architectures for stock market forecasting
inferred← citeshttps://doi.org/10.1016/b978-012554157-2/50001-8openalex-snapshot
Automated Visual Inspection and Artificial Intelligence
inferred← citeshttps://doi.org/10.1016/j.eswa.2008.06.063openalex-snapshot
Ameva: An autonomous discretization algorithm
inferred← citeshttps://doi.org/10.1016/j.ins.2003.03.015openalex-snapshot
CLIP4: Hybrid inductive machine learning algorithm that generates inequality rules
inferred← citeshttps://doi.org/10.1016/j.ins.2007.09.004openalex-snapshot
A discretization algorithm based on Class-Attribute Contingency Coefficient
inferred← citeshttps://doi.org/10.1016/j.iot.2020.100237openalex-snapshot
Requirements for distributed task placement in the fog
inferred← citeshttps://doi.org/10.1016/j.procs.2014.05.315openalex-snapshot
Improve the Classifier Accuracy for Continuous Attributes in Biomedical Datasets Using a New Discretization Method
inferred← citeshttps://doi.org/10.1016/s0169-7161(04)24002-0openalex-snapshot
From Data Mining to Knowledge Mining
inferred← citeshttps://doi.org/10.1017/s0269888910000329openalex-snapshot
Discretization as the enabling technique for the Naïve Bayes and semi-Naïve Bayes-based classification
inferred← citeshttps://doi.org/10.1023/a:1007677805582openalex-snapshot
LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning
inferred← citeshttps://doi.org/10.1109/cec.2002.1006992openalex-snapshot
A preliminary study of learnable evolution methodology implemented with C4.5
inferred← citeshttps://doi.org/10.1109/cec.2008.4631237openalex-snapshot
The simplest evolution/learning hybrid: LEM with KNN
inferred← citeshttps://doi.org/10.1109/fskd.2007.129openalex-snapshot
A Top-Down and Greedy Method for Discretization of Continuous Attributes
inferred← citeshttps://doi.org/10.1109/icmla.2004.1383520openalex-snapshot
Reducing complexity of rule based models via meta mining
inferred← citeshttps://doi.org/10.1109/icmla.2008.29openalex-snapshot
Comparative Analysis of the Impact of Discretization on the Classification with Naïve Bayes and Semi-Naïve Bayes Classifiers
inferred← citeshttps://doi.org/10.1109/mis.2007.19openalex-snapshot
A Heuristic Approach to Learning Rules from Fuzzy Databases
inferred← citeshttps://doi.org/10.1109/tkde.2004.1269594openalex-snapshot
CAIM discretization algorithm
inferred← citeshttps://doi.org/10.1109/tkde.2011.260openalex-snapshot
The Minimum Consistent Subset Cover Problem: A Minimization View of Data Mining
inferred← citeshttps://doi.org/10.1109/tsmcb.2005.852983openalex-snapshot
Highly scalable and robust rule learner: performance evaluation and comparison
inferred← citeshttps://doi.org/10.1145/1046456.1046467openalex-snapshot
A critical review of multi-objective optimization in data mining
inferred← citeshttps://doi.org/10.1145/2594473.2594475openalex-snapshot
Comprehensible classification models
inferred← citeshttps://doi.org/10.13021/mars/3409openalex-snapshot
Learning User Models for Computer Intrusion Detection: Preliminary Results from Natural Induction Approach
inferred← citeshttps://doi.org/10.13021/mars/3480openalex-snapshot
Discovering Multidimensional Patterns in Large Datasets Using Knowledge Scouts
inferred← citeshttps://doi.org/10.13021/mars/3561openalex-snapshot
Initial Considerations toward Knowledge Mining
inferred← citeshttps://doi.org/10.14569/ijacsa.2021.0121215openalex-snapshot
Low Time Complexity Model for Email Spam Detection using Logistic Regression
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3342644/v1openalex-snapshot
Multi-Category Prediction of Students’ Academic Performance Using Machine Learning: For Students Joining Higher Educational Institution in Ethiopia
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3342736/v1openalex-snapshot
Multi-Category Prediction of Students’ Academic Performance Using Machine Learning: For Students Joining Higher Educational Institutions in Ethiopia
inferred← citeshttps://doi.org/10.3233/fi-2000-41404openalex-snapshot
Building Knowledge Scouts Using KGL Metalanguage
inferred← citeshttps://doi.org/10.4304/jcp.9.8.1880-1885openalex-snapshot
The Influence of Inconsistent Data on Cost-Sensitive Classification Using Prism Algorithms: An Empirical Study
inferred← citeshttps://doi.org/10.48550/arxiv.1906.06816openalex-snapshot
A new approach to forecast service parts demand by integrating user preferences into multi-objective optimization
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.