-
Bao, Z.; Han, Z.: What drives users' participation in online social Q&A communities? : an empirical study based on social cognitive theory (2019)
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- Date
- 20. 1.2015 18:30:22
-
Engerer, V.: Metapher und Wissenstransfers im informationsbezogenen Diskurs (2013)
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- Abstract
- Der vorliegende Beitrag1 ist ein Versuch, Eigenschaften von Schöns generativer Metapher auf das "statische" Resultat als Fachterminologie, entstanden durch Übertragung eines wissenschaftlichen Bereiches in einen anderen, anzuwenden. Metapher gilt in diesem Bereich als wissenstransferierendes Verfahren der Übertragung von Konzepten einer Disziplin auf eine andere. Weiterhin wird Metapher als Teil des sprachlichen Jargons in der informationswissenschaftlichen und bibliothekarischen Praxis thematisiert. Ein kurzer Durchgang des dänischen bibliotheksmetaphorischen Wortschatzes zeigt u. a., dass in dieser Domäne ein "ontologisches Erfahrungsgefälle" von abstrakt-konkret wirksam ist, da viele bibliothekstechnische, computer-interaktionsbezogene und informationswissenschaftliche Begriffe mit Hilfe konkreterer Konzepte aus besser verstandenen Domänen, z. B. dem Bereich der Nahrungsaufnahme, erklärt werden. Allerdings scheint auch hier der Anteil "entmetaphorisierter", ehemals metaphorischer Ausdrücke hoch zu sein, wie es bei "abgeschliffenen" Ausdrücken auch in der Gemeinsprache der Fall ist. Die Analyse wird abgerundet mit einem Ausblick auf ein Forschungsgebiet, das in dezidierter Weise von der konzeptuellen Ergiebigkeit des Metaphernbegriffs in der Untersuchung der terminologischen Wissenschaftsbeziehungen Gebrauch macht
- Date
- 22. 3.2013 14:06:49
-
Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014)
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- Date
- 22. 8.2014 17:11:29
-
Luca, E.W. de; Dahlberg, I.: ¬Die Multilingual Lexical Linked Data Cloud : eine mögliche Zugangsoptimierung? (2014)
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- Abstract
- Sehr viele Informationen sind bereits im Web verfügbar oder können aus isolierten strukturierten Datenspeichern wie Informationssystemen und sozialen Netzwerken gewonnen werden. Datenintegration durch Nachbearbeitung oder durch Suchmechanismen (z. B. D2R) ist deshalb wichtig, um Informationen allgemein verwendbar zu machen. Semantische Technologien ermöglichen die Verwendung definierter Verbindungen (typisierter Links), durch die ihre Beziehungen zueinander festgehalten werden, was Vorteile für jede Anwendung bietet, die das in Daten enthaltene Wissen wieder verwenden kann. Um eine semantische Daten-Landkarte herzustellen, benötigen wir Wissen über die einzelnen Daten und ihre Beziehung zu anderen Daten. Dieser Beitrag stellt unsere Arbeit zur Benutzung von Lexical Linked Data (LLD) durch ein Meta-Modell vor, das alle Ressourcen enthält und zudem die Möglichkeit bietet sie unter unterschiedlichen Gesichtspunkten aufzufinden. Wir verbinden damit bestehende Arbeiten über Wissensgebiete (basierend auf der Information Coding Classification) mit der Multilingual Lexical Linked Data Cloud (basierend auf der RDF/OWL-Repräsentation von EuroWordNet und den ähnlichen integrierten lexikalischen Ressourcen MultiWordNet, MEMODATA und die Hamburg Metapher DB).
- Date
- 22. 9.2014 19:00:13
-
Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
-
Taheri, S.M.; Shahrestani, Z.; Nezhad, M.H.Y.: Switching languages and the national content consortiums : an overview on the challenges of designing an Iranian model (2014)
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- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
-
Costas, R.; Zahedi, Z.; Wouters, P.: ¬The thematic orientation of publications mentioned on social media : large-scale disciplinary comparison of social media metrics with citations (2015)
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- Date
- 20. 1.2015 18:30:22
-
Osinska, V.; Kowalska, M.; Osinski, Z.: ¬The role of visualization in the shaping and exploration of the individual information space : part 1 (2018)
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- Date
- 21.12.2018 17:22:13
-
Jiang, Z.; Gu, Q.; Yin, Y.; Wang, J.; Chen, D.: GRAW+ : a two-view graph propagation method with word coupling for readability assessment (2019)
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- Date
- 15. 4.2019 13:46:22
-
Carevic, Z.; Krichel, T.; Mayr, P.: Assessing a human mediated current awareness service (2015)
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-
Zhang, Z.; Zhang, Z.; Law, R.: Editorial responsiveness, journal quality, and total review time : an empirical analysis (2012)
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-
Hahn, M.; Neumann, J.; Razum, M.: RADAR - Ein Forschungsdaten-Repositorium als Dienstleistung für die Wissenschaft (2014)
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- Abstract
- Die Nachvollziehbarkeit und Reproduzierbarkeit wissenschaftlicher Erkenntnisse basieren zunehmend auf digitalen Daten. Deren Publikation, Verfügbarkeit und Nachnutzung muss im Rahmen guter wissenschaftlicher Praxis gewährleistet werden. Das Projekt RADAR geht diese Herausforderung durch die Etablierung einer generischen Infrastruktur für die Archivierung und Publikation von Forschungsdaten an. Es richtet sich an Wissenschaftler (z. B. in Projekten) und Institutionen (z. B. Bibliotheken) mit einem zweistufigen Ansatz: ein disziplinübergreifendes Einstiegsangebot zur formatunabhängigen Datenarchivierung mit minimalem Metadatensatz und ein höherwertiges Angebot mit integrierter Datenpublikation. Thematisch legt RADAR den Schwerpunkt auf die »small sciences«, in denen Forschungsdateninfrastrukturen meist noch fehlen. RADAR erlaubt eine temporäre oder - im Falle einer Datenpublikation - zeitlich unbegrenzte Datenarchivierung. Das angestrebte Geschäftsmodell zielt auf einen sich selbst tragenden Betrieb mit einer Kombination aus Einmalzahlungen und institutionellen Angeboten ab. RADAR ist als ein Baustein der internationalen Informationsinfrastruktur geplant, der sich über Schnittstellen auch in Dienste Dritter integrieren lässt.
-
Zhang, J.; Yu, Q.; Zheng, F.; Long, C.; Lu, Z.; Duan, Z.: Comparing keywords plus of WOS and author keywords : a case study of patient adherence research (2016)
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-
Ren, P.; Chen, Z.; Ma, J.; Zhang, Z.; Si, L.; Wang, S.: Detecting temporal patterns of user queries (2017)
0.03
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Xie, Z.; Ouyang, Z.; Li, J.; Dong, E.: Modelling transition phenomena of scientific coauthorship networks (2018)
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-
He, Z.; Lei, Z.; Wang, D.: Modeling citation dynamics of "atypical" articles (2018)
0.03
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-
Beutelspacher, L.: Fördern Web 2.0 und mobile Technologien das Lernen? : Ein Bericht über die ICT 2011 in Hongkong (2011)
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- Abstract
- Plattformen für Blended Learning, Lernsysteme (wie Moodle), Dienste im Web 2.0 (z. B. Facebook), ePortfolio-Systeme (beispielsweise Mahara), Verfilmungen von Lehrveranstaltungen und weitere Informationsdienste haben breite Anwendung in der Lehre gefunden. Durch das Angebot mobiler Endgeräte (Smartphones, Tablet-Rechner und Laptops) werden die Dienste zunehmend mobil genutzt. Dieser Bericht gibt in informationswissenschaftlicher Perspektive Forschungsergebnisse wieder, die auf der 6. ICT Konferenz in Hongkong "Education unplugged: Mobile Technologies and Web 2.0" (Juli 2011) vorgetragen worden sind.
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Fassbender, J.: ¬Die Register des Buchinhalts : Register oder Konkordanz (2011)
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- Abstract
- Angesichts der wachsenden Zahl von Fachbüchern, die entweder gar kein Sachregister haben oder deren Register nur von schlechter bis indiskutabeler Qualität sind - z. B. automatisch erzeugte Konkordanzen oder eingebettete Register (Index-Marken im Text mit oft übersehenen Nachteilen für die Qualität) -, sieht sich das Deutsche Netzwerk der Indexer zu einem Plädoyer für gute Register veranlasst.
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Rösch, B.: Wie interagieren Nutzer mit Text- und Bildinformationen in einem Wikipedia-Artikel? (2015)
0.03
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- Abstract
- Das Dissertationsprojekt mit dem Arbeitstitel "Text-Bild-Verhältnis in der Online-Enzyklopädie Wikipedia" untersucht die Gestaltung von Text- und Bildelementen in ausgewählten Wikipedia Artikeln und deren Einfluss auf das Rezeptionsverhalten von Nutzern. Als Erhebungsmethodik von Nutzerdaten kamen Experimente zum Blickverhalten, Fragebögen und Wissenstests zum Einsatz. Ziel ist es, Zusammenhänge zwischen der Nutzung von Text- und Bildinformationen und verschiedenen Parametern (wie z. B. Lerntyp, Vorwissen, Studienfach) zu finden.
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Gnoli, C.; Ledl, A.; Park, Z.; Trzmielewski, M.: Phenomenon-based vs. disciplinary classification : possibilities for evaluating and for mapping (2018)
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