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dc.contributor.authorChaleplioglou, Artemis-
dc.contributor.authorPapavlasopoulos, Sozon-
dc.contributor.authorPoulos, Marios-
dc.date.accessioned2023-10-20T13:20:57Z-
dc.date.available2023-10-20T13:20:57Z-
dc.date.issued2019-
dc.identifierscopus-85148861079-
dc.identifier.issn2415-1521-
dc.identifier.issn1991-8755-
dc.identifier.other85148861079-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/568-
dc.description.abstractThe Semantic web offers the intelligent algorithms that could logical analyze scholarly data and retrieve accurate results in scientific research queries. It is based on the generation of ontologies that describe particular knowledge domains. The building of a new ontology is a challenging and demanding approach. Herein, we enable the Hirsch index (h-index) to define the critical terms needed for the description of the cardiology domain. To this end we generated a master vocabulary to describe cardiology derived from relative textbooks by allowing duplicates. More than 56,000 unique terms were collected. The frequency of appearances of each term was used as the sole criterion for the evaluation of its importance in the cardiology domain description. The power regression (log-log) model best fits to these data compared to different nonlinear regression models. Therefore, we apply the h-index function to define the sufficient number of the multiple appeared cardiology terms that could describe this particular scientific field. We found that the hindex for the cardiology terms is 68, indicating the number of terms appearing equally or more than 68 times in the corpus of cardiology textbooks. The definite integral of the power function between the terms and their repeats for the 68 terms was found to represent 70% of the total area under curve. Thus, approximately 1.5‰ of the unique terms indexed in the Cardiology textbooks may be used as the core for the development of a cardiology ontology. We propose that this methodology may serve as a road map in similar librarian applications.en_US
dc.language.isoenen_US
dc.relation.ispartofWSEAS Transactions on Computer Researchen_US
dc.subjectBibliometricsen_US
dc.subjectCardiologyen_US
dc.subjectNon-linear regressionen_US
dc.subjectOntologyen_US
dc.subjectSemantic weben_US
dc.titleH-index for the determination of sufficient terms to describe a scientific fielden_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-85148861079-
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume7en_US
dc.identifier.spage51en_US
dc.identifier.epage55en_US
dc.linkhttps://www.wseas.org/multimedia/journals/computerresearch/2019/a165118-096.pdfen_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-6519-7428-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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