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Using Context-Aware...
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Kastrati, Zenun,1984-Gjøvik University College, Norway
(author)
Using Context-Aware and Semantic Similarity Based Model to Enrich Ontology Concepts
- Article/chapterEnglish2015
Publisher, publication year, extent ...
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2015-06-04
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Cham :Springer,2015
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printrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:lnu-89060
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https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-89060URI
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https://doi.org/10.1007/978-3-319-19581-0_11DOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:kon swepub-publicationtype
Notes
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Domain ontologies are a good starting point to model in a formal way the basic vocabulary of a given domain. However, in order for an ontology to be usable in real applications, it has to be supplemented with lexical resources of this particular domain. The learning process of enriching domain ontologies with new lexical resources employed in the existing approaches takes into account only the contextual aspects of terms and does not consider their semantics. Therefore, this paper proposes a new objective metric namely SEMCON which combines contextual as well as semantic information of terms to enriching the domain ontology with new concepts. The SEMCON defines the context by first computing an observation matrix which exploits the statistical features such as frequency of the occurrence of a term, term’s font type and font size. The semantics is then incorporated by computing a semantic similarity score using lexical database WordNet. Subjective and objective experiments are conducted and results show an improved performance of SEMCON compared with tf*idf and $$\chi ^2$$.
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Yayilgan, Sule YildirimGjøvik University College, Norway
(author)
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Imran, Ali ShariqGjøvik University College, Norway
(author)
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Gjøvik University College, Norway
(creator_code:org_t)
Related titles
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In:Natural Language Processing and Information SystemsCham : Springer, s. 137-14397833191958039783319195810
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