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  1. Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023) 0.02 
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    Date
    22. 6.2023 14:55:20
  2. Ilhan, A.; Fietkiewicz, K.J.: Data privacy-related behavior and concerns of activity tracking technology users from Germany and the USA (2021) 0.02 
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    Abstract
    Purpose This investigation aims to examine the differences and similarities between activity tracking technology users from two regions (the USA and Germany) in their intended privacy-related behavior. The focus lies on data handling after hypothetical discontinuance of use, data protection and privacy policy seeking, and privacy concerns. Design/methodology/approach The data was collected through an online survey in 2019. In order to identify significant differences between participants from Germany and the USA, the chi-squared test and the Mann-Whitney U test were applied. Findings The intensity of several privacy-related concerns was significantly different between the two groups. The majority of the participants did not inform themselves about the respective data privacy policies or terms and conditions before installing an activity tracking application. The majority of the German participants knew that they could request the deletion of all their collected data. In contrast, only 35% out of 68 participants from the US knew about this option. Research limitations/implications This study intends to raise awareness about managing the collected health and fitness data after stopping to use activity tracking technologies. Furthermore, to reduce privacy and security concerns, the involvement of the government, companies and users is necessary to handle and share data more considerably and in a sustainable way. Originality/value This study sheds light on users of activity tracking technologies from a broad perspective (here, participants from the USA and Germany). It incorporates not only concerns and the privacy paradox but (intended) user behavior, including seeking information on data protection and privacy policy and handling data after hypothetical discontinuance of use of the technology.
    Date
    20. 1.2015 18:30:22
  3. Diedrichs, R.; Goebel, R.: K10plus - Technik und Entwicklung (2020) 0.01 
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  4. Oduntan, O.; Ruthven, I.: People and places : bridging the information gaps in refugee integration (2021) 0.01 
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  5. Kasprzik, A.: Aufbau eines produktiven Dienstes für die automatisierte Inhaltserschließung an der ZBW : ein Status- und Erfahrungsbericht. (2023) 0.01 
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    Content
    https://www.o-bib.de/bib/article/view/5903. https://doi.org/10.5282/o-bib/5903.
    Source
    o-bib: Das offene Bibliotheksjournal. 10(2023) Nr.1, S.1-13
  6. Vaas, R.: Wo die Wissenschaft endet (2020) 0.01 
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  7. Vaas, R.: Wo endet die Wissenschaft? (2020) 0.01 
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  8. Andersen, R.: ¬Die Intentionsmaschine (2020) 0.01 
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  9. Kleiner, J.; Lorenz, R.: KI mit Bewusstsein? : Künstliche Intelligenz (2024) 0.01 
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  10. Fagundes, P.B.; Freund, G.P.; Vital, L.P.; Monteiro de Barros, C.; Macedo, D.D.J.de: Taxonomias, ontologias e tesauros : possibilidades de contribuição para o processo de Engenharia de Requisitos (2020) 0.01 
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  11. Bergman, O.; Israeli, T.; Whittaker, S.: ¬The scalability of different file-sharing methods (2020) 0.01 
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  12. Yanovsky, S.; Hoernle, N.; Lev, O.; Gal, K.: One size does not fit all : a study of badge behavior in stack overflow (2021) 0.01 
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  13. Suissa, O.; Elmalech, A.; Zhitomirsky-Geffet, M.: Text analysis using deep neural networks in digital humanities and information science (2022) 0.01 
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  14. Suominen, O.; Koskenniemi, I.: Annif Analyzer Shootout : comparing text lemmatization methods for automated subject indexing (2022) 0.01 
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  15. Fuhr, N.: Modelle im Information Retrieval (2023) 0.01 
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    Abstract
    Information-Retrieval-Modelle -(IR-Modelle) spezifizieren, wie zu einer gegebenen Anfrage die Antwortdokumente aus einer Dokumentenkollektion bestimmt werden. Ausgangsbasis jedes Modells sind dabei zunächst bestimmte Annahmen über die Wissensrepräsentation (s. Teil B Methoden und Systeme der Inhaltserschließung) von Fragen und Dokumenten. Hier bezeichnen wir die Elemente dieser Repräsentationen als Terme, wobei es aus der Sicht des Modells egal ist, wie diese Terme aus dem Dokument (und analog aus der von Benutzenden eingegebenen Anfrage) abgeleitet werden: Bei Texten werden hierzu häufig computerlinguistische Methoden eingesetzt, aber auch komplexere automatische oder manuelle Erschließungsverfahren können zur Anwendung kommen. Repräsentationen besitzen ferner eine bestimmte Struktur. Ein Dokument wird meist als Menge oder Multimenge von Termen aufgefasst, wobei im zweiten Fall das Mehrfachvorkommen berücksichtigt wird. Diese Dokumentrepräsentation wird wiederum auf eine sogenannte Dokumentbeschreibung abgebildet, in der die einzelnen Terme gewichtet sein können. Im Folgenden unterscheiden wir nur zwischen ungewichteter (Gewicht eines Terms ist entweder 0 oder 1) und gewichteter Indexierung (das Gewicht ist eine nichtnegative reelle Zahl). Analog dazu gibt es eine Fragerepräsentation; legt man eine natürlichsprachige Anfrage zugrunde, so kann man die o. g. Verfahren für Dokumenttexte anwenden. Alternativ werden auch grafische oder formale Anfragesprachen verwendet, wobei aus Sicht der Modelle insbesondere deren logische Struktur (etwa beim Booleschen Retrieval) relevant ist. Die Fragerepräsentation wird dann in eine Fragebeschreibung überführt.
  16. Mödden, E.; Dreger, A.; Hommes, K.P.; Mohammadianbisheh, N.; Mölck, L.; Pinna, L.; Sitte-Zöllner, D.: ¬Der Weg zur Gründung der AG Erschließung ÖB-DNB und die Entwicklung eines maschinellen Verfahrens zur Verschlagwortung der Kinder- und Jugendliteratur mit GND-Vokabular (2020) 0.01 
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    Content
    https://www.o-bib.de/article/view/5637. https://doi.org/10.5282/o-bib/5637.
    Source
    o-bib: Das offene Bibliotheksjournal. 7(2020) Nr.4, S.1-9
  17. Herb, U.; Geith, U.: Kriterien der qualitativen Bewertung wissenschaftlicher Publikationen : Befunde aus dem Projekt visOA (2020) 0.01 
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  18. Butlin, P.; Long, R.; Elmoznino, E.; Bengio, Y.; Birch, J.; Constant, A.; Deane, G.; Fleming, S.M.; Frith, C.; Ji, X.; Kanai, R.; Klein, C.; Lindsay, G.; Michel, M.; Mudrik, L.; Peters, M.A.K.; Schwitzgebel, E.; Simon, J.; VanRullen, R.: Consciousness in artificial intelligence : insights from the science of consciousness (2023) 0.01 
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  19. Wiesenmüller, H.: Formale Erschließung (2023) 0.01 
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    Abstract
    Bei der formalen Erschließung bzw. Formalerschließung, die auch als formale Analyse, formale Erfassung, Formalbeschreibung oder (Formal-)Katalogisierung bezeichnet wird, "werden Ressourcen gemäß festgelegten Regeln nach äußerlichen, formalen Kriterien beschrieben und auffindbar gemacht". Diese Ressourcen können alle Arten von physischen und digitalen Objekten sein, die z. B. in Bibliotheken, Archiven, Museen oder Dokumentationsstellen gesammelt oder verzeichnet werden. Formale Aspekte bei einem gedruckten Buch sind u. a. der*die Autor*in, der Titel, der Verlag, das Erscheinungsdatum, der Umfang und die ISBN. Bei einer Skulptur sind es u. a. der*die Künstler*in, das Entstehungsdatum, Werkstoff und Technik, die Maße und die Besitzgeschichte. Bei einem im Internet zur Verfügung gestellten digitalen Foto sind es u. a. der*die Fotograf*in, der Zeitpunkt der Aufnahme und die Koordinaten des Aufnahmeorts, technische Daten zur Aufnahme (z. B. Belichtungszeit), der Dateiname, das Dateiformat und die Dateigröße sowie die URL und ggf. ein Persistent Identifier (z. B. DOI oder URN).
  20. Netzsch, R.: Müssen wir umdenken - und wenn ja, wie? (2021) 0.01 
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