Analogical Retrieval

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Title: Analogical Retrieval
Authors: O'Keeffe, DervlaCostello, Fintan
Permanent link: http://hdl.handle.net/10197/12365
Date: 29-Nov-2007
Online since: 2021-07-30T11:21:44Z
Abstract: We observe that thus far all computational models of analogy have modelled memory as a set of disjoint, encapsulated, domains. As there does not appear to be any psychological evidence for modelling memory in this way, we suggest that a more realistic model of analogy could be constructed if memory was modelled as one large data structure. We argue that the retrieval sub-process of analogy may not be independent of the mapping sub-process, and that both processes may well be governed by structural similarity. We describe a computational model of analogy which incorporates these three ideas; it models mapping and retrieval together, uses structural similarity to govern matching, and models memory as one large data structure. Retrieval in this system corresponds to the searching of the data structure for analogical matches to a supplied probe. We suggest a practical and efficient algorithm for such retrieval.
Funding Details: European Commission
Type of material: Technical Report
Publisher: University College Dublin. School of Computer Science and Informatics
Series/Report no.: UCD CSI Technical Reports; ucd-csi-2007-11
Copyright (published version): 2007 the Authors
Keywords: AnalogyMemoryComputational modelsSearch algorithms
Other versions: https://web.archive.org/web/20080226040105/http:/csiweb.ucd.ie/Research/TechnicalReports.html
Language: en
Status of Item: Not peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science and Informatics Technical Reports

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