Maguire, Phil and Maguire, Rebecca and Cater, Arthur (2008) A Computational Model of Conceptual Combination. Proceedings of the Annual Meeting of the Cognitive Science Society, 30. pp. 59-64. ISSN 1069-7977

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Abstract

We describe the Interactional-Constraint (ICON) model of conceptual combination. This model is based on the idea that combinations are interpreted by incrementally constraining the range of interpretation according to the interacting influence of both constituent nouns. ICON consists of a series of discrete stages, combining data from the British National Corpus, the WordNet lexicon and the Web to predict the dominant interpretation of a combination and a range of factors relating to ease of interpretation. One of the major advantages of the model is that it does not require a tailored knowledge base, thus broadening its scope and utility. We evaluate ICON’s reliability and find that it is accurate in predicting word senses and relations for a wide variety of combinations. However, its ability to predict ease of interpretation is poor. The implications for models of conceptual combination are discussed.

Item Type:	Article
Additional Information:	Suggested citation: Maguire, P., Maguire, R., & Cater, A. W. (2008). A Computational Model of Conceptual Combination. Proceedings of the Annual Meeting of the Cognitive Science Society, 30. Retrieved from https://escholarship.org/uc/item/07f9z4v4
Keywords:	Conceptual combination; noun-noun compounds; paraphrase frequencies; WordNet; language comprehension;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Psychology
Item ID:	10332
Depositing User:	Phil Maguire
Date Deposited:	17 Dec 2018 16:01
Journal or Publication Title:	Proceedings of the Annual Meeting of the Cognitive Science Society
Publisher:	Cognitive Science Society
Refereed:	Yes
URI:
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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