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Automatically Enriching Domain Ontologies for Document Classification
Norwegian University of Science and Technology (NTNU), Norway.ORCID iD: 0000-0002-0199-2377
Norwegian University of Science and Technology (NTNU), Norway.
Norwegian University of Science and Technology (NTNU), Norway.
2016 (English)In: WIMS '16: Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics / [ed] Rajendra Akerkar, Michel Plantié, Sylvie Ranwez, Sébastien Harispe, Anne Laurent, Patrice Bellot, Jacky Montmain, François Trousset, Association for Computing Machinery (ACM), 2016, p. 1-4, article id 29Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The ontology-based document classification approach relies on the content meanings of a given domain exploited and captured using the ontologies of this particular domain. Domain ontologies consist of a set of concepts and relations which links these concepts. However, they often do not provide an in-depth coverage of concepts thereby limiting their use in some subdomain applications. Therefore, the techniques for enhancing ontologies, particularly ontology enrichment, have emerged as an essential prerequisite for ontology-based applications. In this paper, we propose a new objective metric called SEMCON to enrich the domain ontology with new terms. To achieve this, SEMCON combines semantic as well as contextual information of terms within the text documents. Experiments are conducted to demonstrate the applicability of the proposed model and the obtained results from the funding domain show that document classification achieved better performance using the enriched ontology in contrast to using the baseline ontology.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2016. p. 1-4, article id 29
Keywords [en]
Contextual information, Document classification, Ontology enrichment, SEMCON, Semantic information
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-89051DOI: 10.1145/2912845.2912875OAI: oai:DiVA.org:lnu-89051DiVA, id: diva2:1350212
Conference
WIMS '16: International Conference on Web Intelligence, Mining and Semantics, Nîmes, France, June, 2016
Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2021-05-05Bibliographically approved

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Kastrati, Zenun

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf