The use of situation theory in context modeling
dc.citation.epage | 438 | en_US |
dc.citation.issueNumber | 3 | en_US |
dc.citation.spage | 427 | en_US |
dc.citation.volumeNumber | 13 | en_US |
dc.contributor.author | Akman, V. | en_US |
dc.contributor.author | Surav, M. | en_US |
dc.date.accessioned | 2016-02-08T10:47:43Z | |
dc.date.available | 2016-02-08T10:47:43Z | en_US |
dc.date.issued | 1997 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | At the heart of natural language processing is the understanding of context dependent meanings This paper presents a preliminary model of formal contexts based on situation theory. It also gives a worked-out example to show the use of contexts in lifting, i.e., how propositions holding in a particular context transform when they are moved to another context. This is useful in NLP applications where preserving meaning is a desideratum. | en_US |
dc.identifier.doi | 10.1111/0824-7935.00046 | en_US |
dc.identifier.eissn | 1467-8640 | en_US |
dc.identifier.issn | 0824-7935 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/25612 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Wiley-Blackwell Publishing, Inc. | en_US |
dc.relation.isversionof | https://doi.org/10.1111/0824-7935.00046 | en_US |
dc.source.title | Computational Intelligence | en_US |
dc.subject | Commonsense Reasoning | en_US |
dc.subject | Context | en_US |
dc.subject | Knowledge Representation | en_US |
dc.subject | Lifting | en_US |
dc.subject | Natural Language Processing | en_US |
dc.subject | Situation Theory | en_US |
dc.subject | Context Sensitive Languages | en_US |
dc.subject | Natural Language Processing Systems | en_US |
dc.title | The use of situation theory in context modeling | en_US |
dc.type | Article | en_US |
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