Show simple item record De Silva, NHND Perera, AS Maldeniya, MKDT 2014-06-26T11:42:28Z 2014-06-26T11:42:28Z 2014-06-26
dc.description.abstract Word lists that contain closely related sets of words is a critical requirement in machine understanding and processing of natural languages. Creating and maintaining such closely related word lists is a critical and complex process that requires human input and carried out manually in the absence of tools. We describe a supervised learning mechanism which employs a word ontology to expand word lists containing closely related sets of words. The approach described in this paper uses two novel supervised learning techniques that complement each other for the purpose of expanding existing lists of related words. Expanding concept variable lists of RelEx2Frame component of OpenCog Artificial General Intelligence Framework using WordNet is used as a proof of concept. Intervention of this project would enable OpenCog applications to attempt to understand words that they were not able to understand before, due to the limited size of existing lists of related words. en_US
dc.language.iso en en_US
dc.title Semi-supervised algorithm for concept ontology based word set expansion en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Computer Science and Engineering en_US
dc.identifier.year 2013 en_US
dc.identifier.conference International Conference on Advances in ICT for Emerging Regions, ICTer 2013 en_US Colombo en_US
dc.identifier.pgnos pp. 125-131 en_US en_US

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