Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/15756
Title: | An Ontological Approach to the Extraction of Figures of Speech | Authors: | Panayiotou, Christiana | Major Field of Science: | Social Sciences | Field Category: | Media and Communications | Keywords: | On- tological analysis;Figures of speech | Issue Date: | 2019 | Source: | 5th International Conference on Artificial Intelligence and Applications | Link: | http://aircconline.com/csit/abstract/v9n14/csit91405.html | Conference: | International Conference on Artificial Intelligence and Applications | Abstract: | The purpose of the current paper is to present an on- tological analysis to the identification of a particular type of prepositional natural language phrases called figures of speech [1] via the identification of inconsis- tencies in ontological concepts. Prepositional noun phrases are used widely in a multiplicity of domains to describe real world events and activities. However, one aspect that makes a prepositional noun phrase poetical is that the latter suggests a semantic relationship between concepts that does not exist in the real world. The current paper discusses how a set of rules based on Wordnet classes and an ontology repre- senting human behavior and properties, can be used to identify figures of speech. It also addresses the problem of inconsistency resulting from the assertion of figures of speech at various levels identifying the problems involved in their representation. Finally, it discusses how a contextualized approach might help to resolve this problem. | URI: | https://hdl.handle.net/20.500.14279/15756 | DOI: | 10.5121/csit.2019.91405 | Rights: | All Rights Reserved ® AIRCC | Type: | Conference Papers | Affiliation : | Cyprus University of Technology | Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
Page view(s) 50
312
Last Week
0
0
Last month
6
6
checked on Dec 22, 2024
Google ScholarTM
Check
Altmetric
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.