Analogical recognition of shape and structure in design drawings
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Proteus: Visuospatial analogy in problem-solving
Knowledge-Based Systems
Finding the odd one out: a fractal analogical approach
C&C '11 Proceedings of the 8th ACM conference on Creativity and cognition
Representation, indexing, and retrieval of biological cases for biologically inspired design
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
A computational model of visual analogies in design
Cognitive Systems Research
Automatic analysis and sketch-based retrieval of architectural floor plans
Pattern Recognition Letters
Graph-based retrieval of building information models for supporting the early design stages
Advanced Engineering Informatics
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The core issue of analogical reasoning is the transfer of relational knowledge from a source case to a target problem. Visual analogical reasoning pertains to problems containing only visual knowledge. Holyoak and Thagard proposed that the retrieval and mapping tasks of analogy in general can be productively viewed as constraint satisfaction problems, and provided connectionist implementations of their proposal. In this paper, we reexamine the retrieval and mapping tasks of analogy in the context of diagrammatic cases, representing the spatial structure of source and target diagrams as semantic networks in which the nodes represent spatial elements and the links represent spatial relations. We use a method of constraint satisfaction with backtracking for the retrieval and mapping tasks, with subgraph isomorphism over a particular domain language as the similarity measure. Results in the domain of 2D line drawings suggest that at least for this domain the above method is quite promising.