Cited by 884Language, Metaphor, and CognitionCategorization, perception, and languageAI-based Problem Solving and Planning

The DOI matches its Crossref record; 11 of the 12 references it cites were found in a registry or an index; none of the 20 sources its claims cite is checked for support yet.

Structure-mapping: A theoretical framework for analogy

Open access
GENTNER, D·1983·Cognitive Science

Abstract

A theory of analogy must describe how the meaning of an analogy is derived from the meanings of its parts. In the structure-mapping theory, the interpretation rules are characterized as implicit rules for mapping knowledge about a base domain into a target domain. Two important features of the theory are (a) the rules depend only on syntactic properties of the knowledge representation, and not on the specific content of the domains; and (b) the theoretical framework allows analogies to be distinguished cleanly from literal similarity statements, applications of abstractions, and other kinds of comparisons. Two mapping principles are described: (a) Relations between objects, rather than attributes of objects, are mapped from base to target; and (b) The particular relations mapped are determined by systematicity, as defined by the existence of higher-order relations.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This paper presents structure-mapping as a framework for how analogies are interpreted, arguing that analogical mapping transfers relations between objects rather than object attributes, and that relations belonging to interconnected higher-order systems are preferred. It distinguishes analogy from literal similarity, abstraction, and mere appearance matches, and cites prior empirical work as support.

Key findings

  • Analogy maps relational predicates from base to target while discarding object attributes; for example, the atom/solar-system analogy maps relations such as revolving around, attraction, and relative mass, but not attributes such as color or temperature.
  • The systematicity principle holds that a predicate is more likely to be mapped if it belongs to a mutually interconnected system of relations, especially higher-order causal or constraint structures; this explains why a relation like “more massive than” is preserved while a formally similar relation like “hotter than” is not.
  • The framework separates comparison types by predicate overlap: literal similarity maps many attributes and many relations; analogy maps few attributes and many relations; abstraction maps few attributes and many relations with abstract base objects; mere appearance maps attributes but not relations; anomaly maps neither.
  • Empirical support is cited from prior studies: subjects’ interpretations of analogical comparisons were predominantly relational, and aptness ratings correlated with the amount of relational information produced; no numeric values are reported in this paper.

Methods

  • Theoretical paper: knowledge is represented as propositional networks with syntactic predicate types—attributes take one argument, relations take two or more, and predicates can be first-order or higher-order.
  • Worked examples (Rutherford atom/solar system, heat/water, arithmetic analogy) are used to derive mapping rules and a taxonomy of domain comparisons.
  • Empirical support is summarized from prior studies in which subjects wrote interpretations of analogical comparisons and naive judges rated assertions as attribute-based or relation-based; developmental and science-learning studies are also cited.

Limitations

  • The paper states a simplifying assumption that the hearer begins with object correspondences and then maps relations; it notes that actual processing order is variable and that object correspondences may be settled only before relational mapping is finished.
  • The paper assumes predicates are carried across as identical matches and notes that treating predicates as merely similar risks an infinite regress.
  • Evident from the text: empirical support is brief and relies on cited studies rather than new experiments or statistics; the paper is primarily theoretical and does not report detailed sample sizes or quantitative results.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/s0364-0213(83)80009-3

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

62 Own interpretation · 13 Not checked yet · 2 Own result · 1 No basis given

Verify all 20 references — free account

Show all 48 claims

  • Probably not a substantial claim. 21
  • It may state two separate claims as one. 8
  • The quote only partly states this claim. 1
30 of 30
  • The authors state this as an assumption.

    Predicates are carried across as identical matches, and similarity can be restated as identity among some number of component predicates.

    “The assumption that predicates are brought across as idenficul matches is crucial to the clarity of this discussion.”
    “I will assume instead that similarity can be restated as identity among some number of component predicates.”
  • The authors state this as an assumption.

    Partial knowledge of a system is often sufficient for a person to gauge its interconnectedness.

    “I make the assumption here that partial knowledge of the system is often sufficient to allow a person to gauge its interconnectedness.”
  • The authors state this as an assumption.

    In comprehending an analogy, the hearer begins with object correspondences and then maps relations across.

    “Yn this discussion I have made the simplifying assumption that, in comprehension of analogy, the hearer starts with the object correspondences and then maps across the relations.”
3 of 3

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Citations

Cites

Show all 12 references

Research works printed but not linked: 7

  1. Rumelhart, D. E., &Norman. D. A. Analogical processes in learning. In J. R. Anderson (Ed.), Cognirive skills and fheir acquisifion. Hillsdale, NJ: Lawrence Erlbaum Associates, 1981.
  2. Schustack, M. W.. & Anderson. J. R. Effects of analogy to prior knowledge on memory for new information. Journal of Verbal Learning and Verbal Behavior, 1979, 18, 565-583.
  3. Steels. L. An applicaiive view of object oriented programming (MIT A.I. Memo No. 15). Cambridge, MA: Massachusetts Institute of Technology, March 1982.
  4. Stevens, A., Collins, A., & Goldin, S. E. Misconceptions in student's understanding. Journal o/Man-Machine Sfudies. 1979, II. 145-156.
  5. Tourangeau, R., & Sternberg, R. J. Aptness in metaphor. Cogniriue Psychology, 1981, 13, 27-55.
  6. Tversky, A. Features of similarity. Psychological Review, 1977, 84, 327-352.
  7. Winston, P. H. Learning and reasoning by analogy. CACM, 1980. 23, No. 12. Winston, P. H. Learning new principles from precedenrs and exercises. (MIT Artificial Intelli- gence Memo No. 632). Cambridge, MA: Massachusetts Institute of Technology, May 1981.

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Metadata

Authors
GENTNER, D.
Corresponding author
GENTNER, D
Venue
Cognitive Science
Publisher
Wiley
Published
1983-06
Volume
7
Issue
2
Pages
155-170
ISSN
0364-0213 (ISSN-L)
OpenAlex
W4229954498
Cited by
816
References
12
Citations by year
2026: 60 · 2025: 55 · 2024: 69 · 2023: 63 · 2022: 50 · 2021: 53 · 2020: 45 · 2019: 38 · 2018: 27 · 2017: 22 · 2016: 28 · 2015: 23 · 2014: 30 · 2013: 17 · 2012: 14
FWCI
5.03
Type
journal article
Language
en
Open access
Locations
Cognitive Science (publishedVersion)
Topics
  • Social Sciences › Linguistics and Language › Language, Metaphor, and Cognition
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
  • Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
Keywords
structure-mapping theory, analogy, analogical reasoning, mapping rules, knowledge representation, systematicity, higher-order relations, abstraction

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