Knowledge representation and discovery for the interaction between syntax and semantics: A case study of must

Progress in Informatics and Computing(2014)

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摘要
Interaction between syntax and semantics has long been a hot issue in the field of linguistics and natural language processing. In this paper, knowledge representation and discovery for the interrelationship between syntactic features and sense selection of English modal verb must is conducted with the approach of formal concept analysis. A formal context with the senses of English modal verb must as the objects and the syntactic features that co-occur with must as the attributes is constructed first, then a structural partial-ordered attribute diagram is generated. Finally, the relation between different syntactic features and meanings of must is found and the knowledge hidden behind the relation is discovered.
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关键词
data mining,knowledge representation,natural language processing,English modal verb,formal concept analysis,interrelationship,knowledge discovery,knowledge representation,must verb,sense selection,structural partial-ordered attribute diagram,syntactic features,syntax-semantic interaction,formal concept analysis,knowledge representation and discovery,structure partial-ordered attribute diagram,syntactic features
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