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Argument-Based Machine Learning

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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.

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What this work says

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

inferredcites →https://doi.org/10.1007/11871842_33openalex-snapshot
Why Is Rule Learning Optimistic and How to Correct It
inferredcites →https://doi.org/10.1007/978-94-017-0456-4_3openalex-snapshot
Logics for Defeasible Argumentation
inferredcites →https://doi.org/10.1007/bf00116835openalex-snapshot
The CN2 Induction Algorithm
inferredcites →https://doi.org/10.1007/bfb0017011openalex-snapshot
Rule induction with CN2: Some recent improvements
inferredcites →https://doi.org/10.1007/s10506-006-9002-4openalex-snapshot
Argument Based Machine Learning Applied to Law
inferredcites →https://doi.org/10.1016/0010-4485(86)90018-7openalex-snapshot
Prolog programming for artificial intelligence
inferredcites →https://doi.org/10.1016/j.artint.2007.04.007openalex-snapshot
Argument based machine learning
inferredcites →https://doi.org/10.1016/s0004-3702(03)00109-7openalex-snapshot
Law, learning and representation
inferredcites →https://doi.org/10.1023/a:1007631014630openalex-snapshot
Multiple Comparisons in Induction Algorithms
inferredcites →https://doi.org/10.1145/1165485.1165532openalex-snapshot
Application of argument based machine learning to law

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-0-387-98197-0openalex-snapshot
Argumentation in Artificial Intelligence
inferred← citeshttps://doi.org/10.1016/j.ins.2019.07.094openalex-snapshot
Argumentation based reinforcement learning for meta-knowledge extraction
inferred← citeshttps://doi.org/10.1016/j.knosys.2019.02.019openalex-snapshot
GuideR: A guided separate-and-conquer rule learning in classification, regression, and survival settings
inferred← citeshttps://doi.org/10.1093/comjnl/bxz156openalex-snapshot
Artificial Intelligence Surpassing Human Intelligence: Factual or Hoax
inferred← citeshttps://doi.org/10.23736/s2724-6329.20.04416-7openalex-snapshot
A new software architecture proposal for an evidence-based Decision Support System in dentistry
inferred← citeshttps://doi.org/10.24963/ijcai.2017/765openalex-snapshot
The Role of Textualisation and Argumentation in Understanding the Machine Learning Process
inferred← citeshttps://doi.org/10.3233/978-1-61499-686-6-219openalex-snapshot
Argumentation for Machine Learning: A Survey
inferred← citeshttps://doi.org/10.33612/diss.506782323openalex-snapshot
Explain what you see
inferred← citeshttps://doi.org/10.47611/jsrhs.v12i1.3998openalex-snapshot
Analyzing the GPT-3 AI’s Ability to Predict the Answer to Algebraical Questions
inferred← citeshttps://doi.org/10.5772/14096openalex-snapshot
Data Mining Techniques for Explaining Social Events
inferred← citeshttps://doi.org/10.70675/287e3bf5z984az4b7azbffaz0e578f463977openalex-snapshot
Transparent approach based on deep learning and multiagent argumentation for hypertension management
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