Enrichment of ontology instances using linked data and supplemental string data

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 35
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKim, Dongjaeko
dc.contributor.authorLee, Dongmanko
dc.contributor.authorKim, Myungchulko
dc.contributor.authorHyun, Soon-Jooko
dc.date.accessioned2023-07-20T09:00:30Z-
dc.date.available2023-07-20T09:00:30Z-
dc.date.created2023-07-07-
dc.date.issued2018-12-
dc.identifier.citation2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018, pp.966 - 971-
dc.identifier.urihttp://hdl.handle.net/10203/310719-
dc.description.abstractVarious emerging applications using IoT require frequent ontology re-construction in ways to enrich the knowledge map. We propose a hybrid approach for a new semi-automated ontology enrichment system which expands the present ontology by using both linked data extracted from other ontology of the same (or similar) application domain and string data crawled from the web. Our system enriches an ontology with new instances of concepts and relations in two phases. First, it extracts new instances and relations from a reference ontology of the same or similar domain. Second, it validates the possible relations between the original instances and the new ones using crawled data from the web search. Our system computes confidence value to check validity of those relations before adding them to the present ontology. Our experiment demonstrates that the proposed two-phase hybrid approach achieves improved efficiency and accuracy for enriching ontology instances.-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleEnrichment of ontology instances using linked data and supplemental string data-
dc.typeConference-
dc.identifier.scopusid2-s2.0-85078529130-
dc.type.rimsCONF-
dc.citation.beginningpage966-
dc.citation.endingpage971-
dc.citation.publicationname2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationLas Vegas, NV-
dc.identifier.doi10.1109/CSCI46756.2018.00188-
dc.contributor.localauthorLee, Dongman-
dc.contributor.localauthorHyun, Soon-Joo-
dc.contributor.nonIdAuthorKim, Dongjae-
dc.contributor.nonIdAuthorKim, Myungchul-
Appears in Collection
CS-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0