Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/77551
Type: Conference paper
Title: Strong structure in weak semantic similarity: a graph based account
Author: De Deyne, S.
Navarro, D.
Perfors, A.
Storms, G.
Citation: Proceedings of the 34th Annual Conference of the Cognitive Science Society, 2012 / pp.1464-1469
Publisher: Cognitive Science Society
Publisher Place: USA
Issue Date: 2012
ISBN: 9780976831884
Conference Name: Annual Conference of the Cognitive Science Society (CogSci) (01 Aug 2012 : Sapporo, Japan)
Statement of
Responsibility: 
Simon De Deyne, Daniel J. Navarro, Amy Perfors and Gert Storms
Abstract: Research into word meaning and similarity structure typically focus on highly related entities like CATS and MICE. However, most items in the world are only weakly related. Does our representation of the world encode any information about these weak relationships? Using a three-alternative forced-choice similarity task, we investigate to what extent people agree on the relationships underlying words that are only weakly related. These experiments show systematic preferences about which items are perceived as most similar. A similarity measure based on semantic network graphs gives a good account for human ratings of weak similarity.
Keywords: Similarity; semantic networks; word associations
Rights: Copyright status unknown
RMID: 0020127079
Published version: http://mindmodeling.org/cogsci2012/papers/0260/index.html
Appears in Collections:Psychology publications

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