University of Bahrain
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Enhancing Ontology by Integrating Facts from Unstructured Data and Mapping with Linguistic Knowledge

Show simple item record Devi, Runumi Mehrotra, Deepti 2019-10-30T05:57:08Z 2019-10-30T05:57:08Z 2019-11-01
dc.identifier.issn 2210-142X
dc.description.abstract Ontology plays a crucial role in the growth of semantic web by providing a domain- knowledge resource comprehensible to both humans as well as computers. Knowledge resources can be of two types-taxonomical knowledge supporting description logic in the form of ontology representing a particular domain and linguistic knowledge. An approach is presented in this paper for constructing a third type of knowledge resource(Hybrid) that accommodates variations in the structure as per RDF triple extracted from unstructured corpus and subsequently semantically associating ontological concepts with their linguistic counter-part. The purpose of this knowledge base is to add linguistic expressiveness to conceptual knowledge and to accommodate the dynamic nature of knowledge. Semantic similarity and term coverage are computed between terms(concepts). A case study i.e enhancing a dengue ontology by incorporating RDF triple extracted from patients’ case sheets and semantically associating concepts with WordNet by using similarity and relatedness measures is presented. en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri *
dc.subject Ontology en_US
dc.subject Dengue en_US
dc.subject Knowledge base en_US
dc.subject Semantic similarity en_US
dc.subject WordNet en_US
dc.title Enhancing Ontology by Integrating Facts from Unstructured Data and Mapping with Linguistic Knowledge en_US
dc.volume Volume 8 en_US
dc.issue Issue 6 en_US
dc.contributor.authorcountry India en_US
dc.contributor.authoraffiliation Amity University Uttar Pradesh, India en_US
dc.source.title International Journal of Computing and Digital Systems en_US

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