Publication:
A Similarity Precision for Selecting Ontology Component in an Incomplete Sentence

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dc.ConferencedateFEB 06-07, 2018
dc.ConferencelocationJohor, MALAYSIA
dc.Conferencename3rd International Conference on Soft Computing and Data Mining (SCDM)
dc.contributor.authorHeng, FNRen_US
dc.contributor.authorDeris, MMen_US
dc.contributor.authorBasir, Nen_US
dc.date.accessioned2024-05-29T03:25:40Z
dc.date.available2024-05-29T03:25:40Z
dc.date.issued2018
dc.description.abstractMost of the existing methods focus on extracting concepts and identifying the hierarchy of concepts. However, in order to provide the whole view of the domain, the non-taxonomic relationships between concepts are also needed. Most of extracting techniques for non-taxonomic relation only identify concepts and relations in a complete sentence. However, the domain texts may not be properly presented as some sentences in domain text have missing or unsure term of concepts. This paper proposes a technique to overcome the issue of missing concepts in incomplete sentence. The proposed technique is based on the similarity precision for selecting missing concept in incomplete sentence. The approach has been tested with Science corpus. The experiment results were compared with the results that have been evaluated by the domain experts manually. The result shows that the proposed method has increased the relationships of domain texts thus providing better results compared to several existing method.
dc.identifier.doi10.1007/978-3-319-72550-5_10
dc.identifier.epage104
dc.identifier.isbn2194-5365
dc.identifier.issn2194-5357
dc.identifier.scopusWOS:000434083500010
dc.identifier.spage95
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/12004
dc.identifier.volume700
dc.languageEnglish
dc.language.isoen_US
dc.publisherSpringer International Publishing Agen_US
dc.relation.ispartofRecent Advances On Soft Computing And Data Mining (Scdm 2018)
dc.sourceWeb Of Science (ISI)
dc.subjectOntologyen_US
dc.subjectNon-taxonomic relationen_US
dc.subjectSimilarity precisionen_US
dc.titleA Similarity Precision for Selecting Ontology Component in an Incomplete Sentence
dc.typeProceedings Paperen_US
dspace.entity.typePublication

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