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    Spatial Inference Based on Geometric Proportional Analogies

    Mullally, Emma-Claire and O'Donoghue, Diarmuid (2006) Spatial Inference Based on Geometric Proportional Analogies. Artificial Intelligence Review, 26 (1). pp. 129-140. ISSN 0269-2821

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    We describe an instance-based reasoning solution to a variety of spatial reasoning problems. The solution centers on identifying an isomorphic mapping between labelled graphs that represent some problem data and a known solution instance. We describe a number of spatial reasoning problems that are solved by generating non-deductive inferences, integrating topology with area (and other) features. We report the accuracy of our algorithm on different categories of spatial reasoning tasks from the domain of Geographical Information Science. The generality of our approach is illustrated by also solving geometric proportional (IQ-test type) analogy problems.

    Item Type: Article
    Additional Information: Cite this article as: Mullally, EC. & O’Donoghue, D.P. Artif Intell Rev (2006) 26: 129. doi:10.1007/s10462-007-9043-4
    Keywords: Analogical similarity; Spatial inference; Topographic maps;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8181
    Identification Number:
    Depositing User: Dr. Diarmuid O'Donoghue
    Date Deposited: 26 Apr 2017 14:43
    Journal or Publication Title: Artificial Intelligence Review
    Publisher: Springer Verlag
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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