Publication:
A similarity precision for selecting ontology component in an incomplete sentence

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dc.Conferencecode209769
dc.Conferencedate6 February 2018 through 8 February 2018
dc.Conferencename3rd International Conference on Soft Computing and Data Mining, SCDM 2018
dc.FundingDetailsUniversiti Sains Islam Malaysia Universiti Sains Islam Malaysia
dc.FundingDetailsAcknowledgements. This work was supported under Grant Universiti Sains Islam Malaysia (USIM). Grants: PPP/USG-0116/FST/30/11616.
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.affiliationsUniversiti Tun Hussein Onn Malaysia (UTHM)
dc.contributor.authorHeng F.N.R.en_US
dc.contributor.authorDeris M.M.en_US
dc.contributor.authorBasir N.en_US
dc.date.accessioned2024-05-28T08:32:33Z
dc.date.available2024-05-28T08:32:33Z
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. � 2018, Springer International Publishing AG.
dc.description.natureFinalen_US
dc.description.sponsorshipShahreen Kasim
dc.description.sponsorshipUniversiti Tun Hussein Onn Malaysia
dc.editorAbawajy J.H.Ghazali R.Deris M.M.Nawi N.M.en_US
dc.identifier.doi10.1007/978-3-319-72550-5_10
dc.identifier.epage104
dc.identifier.isbn9783320000000
dc.identifier.issn21945357
dc.identifier.scopus2-s2.0-85041522459
dc.identifier.spage95
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85041522459&doi=10.1007%2f978-3-319-72550-5_10&partnerID=40&md5=2a435fab9093392362c40c9923a369fd
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9026
dc.identifier.volume700
dc.languageEnglish
dc.language.isoen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.sourceScopus
dc.subjectNon-taxonomic relationen_US
dc.subjectOntologyen_US
dc.subjectSimilarity precisionen_US
dc.subjectOntologyen_US
dc.subjectSoft computingen_US
dc.subjectDomain expertsen_US
dc.subjectExtracting concepten_US
dc.subjectNon-taxonomic relationen_US
dc.subjectSimilarity precisionen_US
dc.subjectData miningen_US
dc.titleA similarity precision for selecting ontology component in an incomplete sentence
dc.typeConference Paperen_US
dspace.entity.typePublication

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