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Improving Knowledge Extraction from Texts by Generating Possible Relations

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dc.ConferencecodeInt Assoc Engineers, IAENG, Soc Artificial Intelligence, IAENG, Soc Bioinformat, IAENG, Soc Comp Sci, IAENG, Soc Data Min, IAENG, Soc Elect Engn, IAENG, Soc HIV AIDS, IAENG, Soc Imag Engn, IAENG, Soc Ind Engn, IAENG, Soc Informat Syst Engn, IAENG, Soc internet Comp & Web Serv, IAENG, Soc Mech Engn, IAENG, Soc Operat Res, IAENG, Soc Sci Comp, IAENG, Soc Software Engn, IAENG, Soc Wireless Networks
dc.ConferencedateOCT 25-27, 2017
dc.ConferencelocationSan Francisco, CA
dc.ConferencenameWorld Congress on Engineering and Computer Science, WCES 2017
dc.contributor.authorNabila, NFen_US
dc.contributor.authorBasir, Nen_US
dc.contributor.authorMamat, Aen_US
dc.contributor.authorDenis, MMen_US
dc.date.accessioned2024-05-29T03:27:20Z
dc.date.available2024-05-29T03:27:20Z
dc.date.issued2017
dc.description.abstractExisting research focus on extracting the concepts and relations within a single sentence or in subject-object object pattern. However, a problem arises when either the object or subject of a sentence is "missing" or "uncertain", which will cause the domain texts to be improperly presented as the relationship between concepts is no extracted. This paper proposes a solution for the enrichment of the knowledge of domain text by finding all possible relations. The proposed method suggests the appropriate or the most likely term for an uncertain subject or object of a sentence using the probability theory. In addition, the method can extract the relations between concepts (i.e. subject and object) that appear not only in a single sentence, but also in different sentences by using a synonym of the predicates. The proposed method has been tested and evaluated with a collection of domain texts that describe tourism. Precision, recall, and f-score metrics have been used to evaluate the results of the experiments.
dc.identifier.epage60
dc.identifier.issn2078-0958
dc.identifier.scopusWOS:000418106200012
dc.identifier.spage55
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/12206
dc.languageEnglish
dc.language.isoen_US
dc.publisherInt Assoc Engineers-Iaengen_US
dc.relation.ispartofWorld Congress On Engineering And Computer Science, Wcecs 2017, Vol I
dc.sourceWeb Of Science (ISI)
dc.subjectRelation Extractionen_US
dc.subjectNon-taxonomicen_US
dc.subjectOntologyen_US
dc.titleImproving Knowledge Extraction from Texts by Generating Possible Relations
dc.typeProceedings Paperen_US
dspace.entity.typePublication

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