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dc.contributor.authorΠαπαθεοδώρου, Χρήστοςel_GR
dc.contributor.authorΜητρέλης, Άγγελοςel_GR
dc.contributor.authorΠαπαχριστόπουλος, Λεωνίδαςel_GR
dc.contributor.authorΣφακάκης, Μιχάληςel_GR
dc.contributor.authorΤσάκωνας, Γιάννηςel_GR
dc.contributor.authorMitrelis, Angelosen
dc.contributor.authorPapatheodorou, Christosen
dc.contributor.authorPapachristopoulos, Leonidasen
dc.contributor.authorTsakonas, Giannisen
dc.contributor.authorSfakakis, Michalisen
dc.descriptionΠεριέχει το πλήρες κείμενοel_GR
dc.description.abstractScientific literature is vast and therefore the researchers need knowledge organization systems to index, semantically annotate and correlate their bibliographic sources. Additionally they need methods and tools to discover scientific trends and commonly acceptable practices or areas for further investigation. This paper proposes a clustering-based data mining process to identify research patterns in the digital libraries evaluation domain. The papers published in the proceedings of a well known international conference in the decade 2001-2010 were semantically annotated using the Digital Library Evaluation Ontology (DiLEO). The generated annotations were clustered to portray common evaluation practices. The findings highlight the expressive nature of DiLEO and underline the potential of clustering in the research activities profiling.en
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 7567 LNCS, 2012, Pages 464-473en
dc.titleMining digital library evaluation patterns using a domain ontologyen
dc.subject.uncontrolledtermDigital library evaluationen
dc.subject.uncontrolledtermResearch trends discoveryen
dc.subject.JITAΒιβλιοθήκες ως φυσικές συλλογέςel_GR
dc.subject.JITALibraries as physical collectionsen

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