MURAL - Maynooth University Research Archive Library

    Seeing Things: Inventive Reasoning with Geometric Analogies and Topographic Maps

    O'Donoghue, Diarmuid and Bohan, Amy and Keane, Mark T. (2006) Seeing Things: Inventive Reasoning with Geometric Analogies and Topographic Maps. New Generation Computing, 24 (3). pp. 267-288. ISSN 0288-3635

    Download (1MB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    This paper examines two seemingly unrelated qualitative spatial reasoning domains; geometric proportional analogies and topographic (land-cover) maps. We present a Structure Matching algorithm that combines Gentner’s structuremapping theory with an attributematching process. We use structure matching to solve geometric analogy problems that involve manipulating attribute information, such as colors and patterns. Structure matching is also used to creatively interpret topographic (land-cover) maps, adding a wealth of semantic knowledge and providing a far richer interpretation of the raw data. We return to the geometric proportional analogies, identify alternate attribute matching processes that are required to solve different categories of problems. Finally, we assess some implications for computationally creative and inventive models.

    Item Type: Article
    Additional Information: Cite as: O’Donoghue, D.P., Bohan, A. & Keane, M.T. New Gener Comput (2006) 24: 267.
    Keywords: Intelligent Systems; Geometric Proportional Analogies; Attribute Matching; Topographic Maps; Creative Interpretation;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 10343
    Identification Number:
    Depositing User: Dr. Diarmuid O'Donoghue
    Date Deposited: 20 Dec 2018 17:06
    Journal or Publication Title: New Generation Computing
    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

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads