On the public citation graph

Demand-driven concept formation

0 signed · 51 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-3-642-68826-3_6openalex-snapshot

Automatische Akquisition von inferentiellem Wissen

inferredcites →https://doi.org/10.1007/978-3-642-73005-4_14openalex-snapshot

Higher-order Concepts in a Tractable Knowledge Representation

inferredcites →https://doi.org/10.1007/978-3-662-12405-5openalex-snapshot

Machine Learning

inferredcites →https://doi.org/10.1007/978-3-662-12405-5_11openalex-snapshot

Learning from Observation: Conceptual Clustering

inferredcites →https://doi.org/10.1007/978-3-662-12405-5_15openalex-snapshot

LEARNING EFFICIENT CLASSIFICATION PROCEDURES AND THEIR APPLICATION TO CHESS END GAMES

inferredcites →https://doi.org/10.1007/978-3-662-12405-5_3openalex-snapshot

A COMPARATIVE REVIEW OF SELECTED METHODS FOR LEARNING FROM EXAMPLES

inferredcites →https://doi.org/10.1007/bf00114264openalex-snapshot

Experiments with Incremental Concept Formation: UNIMEM

inferredcites →https://doi.org/10.1007/bf00114265openalex-snapshot

Knowledge Acquisition Via Incremental Conceptual Clustering

inferredcites →https://doi.org/10.1007/bfb0017221openalex-snapshot

An inference engine for representing multiple theories

inferredcites →https://doi.org/10.1007/bfb0017222openalex-snapshot

The acquisition of model-knowledge for a model-driven machine learning approach

inferredcites →https://doi.org/10.1016/0004-3702(85)90005-0openalex-snapshot

Machine learning: An artificial intelligence approach

inferredcites →https://doi.org/10.1016/0004-3702(86)90016-0openalex-snapshot

Variable precision logic

inferredcites →https://doi.org/10.1016/0004-3702(86)90030-5openalex-snapshot

Conceptual clustering of structured objects: A goal-oriented approach

inferredcites →https://doi.org/10.1016/0022-2496(83)90037-8openalex-snapshot

Machine learning: An artificial intelligence approach

inferredcites →https://doi.org/10.1016/0167-7136(83)90132-4openalex-snapshot

A theory and methodology of inductive learning

inferredcites →https://doi.org/10.1016/b978-0-934613-41-5.50011-8openalex-snapshot

MORE ROBUST CONCEPT LEARNING USING DYNAMICALLY – VARIABLE BIAS

inferredcites →https://doi.org/10.1016/b978-0-934613-41-5.50012-xopenalex-snapshot

Incremental Adjustment of Representations for Learning

inferredcites →https://doi.org/10.1016/b978-0-934613-41-5.50035-0openalex-snapshot

Hill-Climbing Theories of Learning

inferredcites →https://doi.org/10.1016/s0020-7373(88)80006-3openalex-snapshot

Design goals for sloppy modeling systems

inferredcites →https://doi.org/10.1016/s0364-0213(83)80002-0openalex-snapshot

Reconstructive Memory: A Computer Model*

inferredcites →https://doi.org/10.1016/s0736-5853(86)80076-4openalex-snapshot

Knowledge Based Systems in Artificial Intelligence

inferredcites →https://doi.org/10.1023/a:1022687019898openalex-snapshot

Editorial: On Machine Learning

inferredcites →https://doi.org/10.1023/a:1022896407371openalex-snapshot

Machine Learning and Concept Formation

inferredcites →https://doi.org/10.1184/r1/6561269openalex-snapshot

The search for regularity : four aspects of scientific discovery

inferredcites →https://doi.org/10.4159/harvard.9780674866270openalex-snapshot

Categories and Concepts

What points at this work

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

inferred← citeshttps://doi.org/10.1007/3-540-44797-0_11openalex-snapshot

Demand-Driven Construction of Structural Features in ILP

inferred← citeshttps://doi.org/10.1007/3-540-55546-3_40openalex-snapshot

Knowledge refinement using Knowledge Acquisition and Machine Learning Methods

inferred← citeshttps://doi.org/10.1007/3-540-56602-3_128openalex-snapshot

On the proper definition of minimality in specialization and theory revision

inferred← citeshttps://doi.org/10.1007/3-540-56602-3_129openalex-snapshot

Predicate invention in inductive data engineering

inferred← citeshttps://doi.org/10.1007/978-3-642-75182-0_8openalex-snapshot

Lernen im geschlossenen Kreislauf

inferred← citeshttps://doi.org/10.1007/978-3-642-77623-6_3openalex-snapshot

Das HALMOR System

inferred← citeshttps://doi.org/10.1007/978-3-642-78545-0_19openalex-snapshot

Neuere Entwicklungen der deklarativen KI-Programmierung

inferred← citeshttps://doi.org/10.1007/bf00992861openalex-snapshot

Interactive concept-learning and constructive induction by analogy

inferred← citeshttps://doi.org/10.1007/bf00993078openalex-snapshot

Balanced cooperative modeling

inferred← citeshttps://doi.org/10.1007/bfb0017001openalex-snapshot

A multistrategy learning approach to domain modeling and knowledge acquisition

inferred← citeshttps://doi.org/10.1007/bfb0017007openalex-snapshot

Application of empirical discovery in knowledge acquisition

inferred← citeshttps://doi.org/10.1007/bfb0017019openalex-snapshot

Acquiring object-knowledge for learning systems

inferred← citeshttps://doi.org/10.1007/bfb0017221openalex-snapshot

An inference engine for representing multiple theories

inferred← citeshttps://doi.org/10.1016/1042-8143(91)90002-5openalex-snapshot

Underlying assumptions of knowledge acquisition and machine learning

inferred← citeshttps://doi.org/10.1016/b978-1-55860-200-7.50081-7openalex-snapshot

Integrity Constraints and Interactive Concept-Learning

inferred← citeshttps://doi.org/10.1016/s0020-7373(88)80006-3openalex-snapshot

Design goals for sloppy modeling systems

inferred← citeshttps://doi.org/10.1017/s0269888900006366openalex-snapshot

A unifying framework for concept-learning algorithms

inferred← citeshttps://doi.org/10.1023/a:1022622132310openalex-snapshot

Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments

inferred← citeshttps://doi.org/10.1023/a:1022664419589openalex-snapshot

Interactive Concept-Learning and Constructive Induction by Analogy

inferred← citeshttps://doi.org/10.1023/a:1022674116380openalex-snapshot

Concept Formation During Interactive Theory Revision

inferred← citeshttps://doi.org/10.1080/08839519408945460openalex-snapshot

KNOWLEDGEABLE LEARNING USING MOBAL: A MEDICAL CASE STUDY

inferred← citeshttps://doi.org/10.1080/09528139208953748openalex-snapshot

Acquiring object-knowledge

inferred← citeshttps://doi.org/10.1109/21.199468openalex-snapshot

Automating knowledge acquisition as extending, updating, and improving a knowledge base

inferred← citeshttps://doi.org/10.13021/mars/3483openalex-snapshot

Constructive Induction: The Key to Design Creativity

inferred← citeshttps://doi.org/10.13021/mars/3571openalex-snapshot

Matching Methods with Problems: A Comparative Analysis of Constructive Induction Approaches

inferred← citeshttps://doi.org/10.5555/777092.777236openalex-snapshot

Mixed-initiative exception-based learning for knowledge base refinement

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.