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Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review

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What this work says

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

inferredcites →https://doi.org/10.1007/978-0-387-09823-4_6openalex-snapshot
Discretization Methods
inferredcites →https://doi.org/10.1007/978-0-387-39252-3openalex-snapshot
Ontology Learning and Population from Text: Algorithms, Evaluation and Applications
inferredcites →https://doi.org/10.1007/978-3-030-01246-5_2openalex-snapshot
Progressive Neural Architecture Search
inferredcites →https://doi.org/10.1007/978-3-030-51924-7_1openalex-snapshot
Agent-Based Explanations in AI: Towards an Abstract Framework
inferredcites →https://doi.org/10.1007/978-3-030-82017-6_20openalex-snapshot
Expectation: Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge
inferredcites →https://doi.org/10.1007/978-3-319-46307-0_29openalex-snapshot
DeepRED – Rule Extraction from Deep Neural Networks
inferredcites →https://doi.org/10.1007/978-3-319-57959-7openalex-snapshot
The EU General Data Protection Regulation (GDPR)
inferredcites →https://doi.org/10.1007/978-3-642-76070-9_6openalex-snapshot
Why Distributed Representation is Inherently Non-Symbolic
inferredcites →https://doi.org/10.1007/978-3-642-76274-1openalex-snapshot
Computational Logic
inferredcites →https://doi.org/10.1007/978-94-015-9833-0_3openalex-snapshot
Higher-Order Logic
inferredcites →https://doi.org/10.1007/s00146-019-00912-zopenalex-snapshot
The new AI spring: a deflationary view
inferredcites →https://doi.org/10.1007/s10710-017-9314-zopenalex-snapshot
Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning
inferredcites →https://doi.org/10.1016/0022-0000(87)90027-4openalex-snapshot
Why horn formulas matter in computer science: Initial structures and generic examples
inferredcites →https://doi.org/10.1016/0950-7051(96)81920-4openalex-snapshot
Survey and critique of techniques for extracting rules from trained artificial neural networks
inferredcites →https://doi.org/10.1016/b978-1-55860-200-7.50040-4openalex-snapshot
ID2-of-3: Constructive Induction of M-of-N Concepts for Discriminators in Decision Trees
inferredcites →https://doi.org/10.1016/b978-155860932-7/50101-1openalex-snapshot
The Tradeoff between Expressiveness and Tractability
inferredcites →https://doi.org/10.1016/c2015-0-00237-4openalex-snapshot
Machine Learning
inferredcites →https://doi.org/10.1016/j.artint.2018.07.007openalex-snapshot
Explanation in artificial intelligence: Insights from the social sciences
inferredcites →https://doi.org/10.1016/j.dss.2010.12.003openalex-snapshot
An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models
inferredcites →https://doi.org/10.1016/j.eswa.2009.10.018openalex-snapshot
Multiple classifier application to credit risk assessment
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.012openalex-snapshot
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
inferredcites →https://doi.org/10.1016/s0004-3702(00)00077-1openalex-snapshot
Symbolic knowledge extraction from trained neural networks: A sound approach
inferredcites →https://doi.org/10.1016/s0022-0000(05)80071-6openalex-snapshot
Datalog vs first-order logic
inferredcites →https://doi.org/10.1038/323533a0openalex-snapshot
Learning representations by back-propagating errors
inferredcites →https://doi.org/10.1038/s42256-019-0048-xopenalex-snapshot
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
inferredcites →https://doi.org/10.1108/k.2003.06732iae.006openalex-snapshot
The Description Logic Handbook – Theory, Implementation and Applications
inferredcites →https://doi.org/10.1109/4235.585893openalex-snapshot
No free lunch theorems for optimization
inferredcites →https://doi.org/10.1109/access.2019.2896880openalex-snapshot
Speech Recognition Using Deep Neural Networks: A Systematic Review
inferredcites →https://doi.org/10.1109/tkde.2017.2754499openalex-snapshot
Knowledge Graph Embedding: A Survey of Approaches and Applications
inferredcites →https://doi.org/10.1109/tkde.2021.3079836openalex-snapshot
Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems
inferredcites →https://doi.org/10.1109/tnnls.2018.2876865openalex-snapshot
Object Detection With Deep Learning: A Review
inferredcites →https://doi.org/10.1109/tnnls.2020.2979670openalex-snapshot
A Survey of the Usages of Deep Learning for Natural Language Processing
inferredcites →https://doi.org/10.1111/j.1467-8640.1987.tb00176.xopenalex-snapshot
Expressiveness and tractability in knowledge representation and reasoning1
inferredcites →https://doi.org/10.1145/2594473.2594475openalex-snapshot
Comprehensible classification models
inferredcites →https://doi.org/10.1145/3097983.3098039openalex-snapshot
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
inferredcites →https://doi.org/10.1145/3233231openalex-snapshot
The Mythos of Model Interpretability
inferredcites →https://doi.org/10.1145/3236009openalex-snapshot
A Survey of Methods for Explaining Black Box Models
inferredcites →https://doi.org/10.1145/3442381.3450068openalex-snapshot
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework
inferredcites →https://doi.org/10.1145/800186.810578openalex-snapshot
The use of theorem-proving techniques in question-answering systems
inferredcites →https://doi.org/10.1177/2053951715622512openalex-snapshot
How the machine ‘thinks’: Understanding opacity in machine learning algorithms
inferredcites →https://doi.org/10.1214/21-ss133openalex-snapshot
Interpretable machine learning: Fundamental principles and 10 grand challenges
inferredcites →https://doi.org/10.1609/aimag.v38i3.2741openalex-snapshot
European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”
inferredcites →https://doi.org/10.2139/ssrn.961358openalex-snapshot
Using Rule Extraction to Improve the Comprehensibility of Predictive Models
inferredcites →https://doi.org/10.2307/2268661openalex-snapshot
On sentences which are true of direct unions of algebras
inferredcites →https://doi.org/10.2307/2272123openalex-snapshot
Fragments of first order logic, I: universal Horn logic
inferredcites →https://doi.org/10.2307/2530946openalex-snapshot
Classification and Regression Trees.
inferredcites →https://doi.org/10.3233/faia210348openalex-snapshot
Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation1
inferredcites →https://doi.org/10.3233/ia-190036openalex-snapshot
On the integration of symbolic and sub-symbolic techniques for XAI: A survey
inferredcites →https://doi.org/10.48550/arxiv.1610.05267openalex-snapshot
Rule Extraction Algorithm for Deep Neural Networks: A Review
inferredcites →https://doi.org/10.5860/choice.32-0639openalex-snapshot
Encyclopedia of software engineering

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

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Intelligent Agents from Symbolic to Neurosymbolic Systems: The Quest for Integration
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Pedagogical Knowledge Extraction from Black-Box Classifiers with DiViNE
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The Missing Link Between Space Law and Artificial Intelligence: A Position Paper on Explainability for Future Intelligent Space Systems
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Unifying Explainable Agency Via a Ladder of Intentions
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Structured Representation Learning from Network Behavior for Attribute-Based Access Control
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inferred← citeshttps://doi.org/10.1016/j.compind.2025.104409openalex-snapshot
Towards trustworthy artificial intelligence for decision-making: A lifecycle perspective on knowledge- and data-driven artificial intelligence systems
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A review of neuro-symbolic AI integrating reasoning and learning for advanced cognitive systems
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112940openalex-snapshot
Large language models as oracles for instantiating ontologies with domain-specific knowledge
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GInGER: Genetic domain partitioning for interpretable rule extraction and induction
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Unfair Inequality in Education: A Benchmark for AI-Fairness Research
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Human-Centered AI in Smart Farming: Toward Agriculture 5.0
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Neuro-Symbolic AI for Supporting Chronic Disease Diagnosis and Monitoring
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Confronting Challenges of the Neuro-Symbolic AI (NSAI) in Human-Centered Computing (HCC), Healthcare, Education and Research, Emphasizing Ethics and Safety- an Interdisciplinary Qualitative Survey
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Ante-Hoc Methods for Interpretable Deep Models: A Survey
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Four Decades of Symbolic Knowledge Extraction from Sub-Symbolic Predictors. A Survey
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Ontology engineering–based large language model revolution in chemical research paradigms
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AI-Driven Cooperative Control for Autonomous Tractors and Implements: A Comprehensive Review
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Bridging Knowledge and Learning: A Multi-Axis Analytical Survey for Neurosymbolic Artificial Intelligence
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