Search (28 results, page 1 of 2)

  • × theme_ss:"Internet"
  • × year_i:[2010 TO 2020}
  1. Ceynowa, K.: Informationsdienste im mobilen Internet : das Beispiel der Bayerischen Staatsbibliothek (2011) 0.02
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    Abstract
    Ausgehend von der Überzeugung, dass der Zugriff auf digitale Information künftig primär,wenn nicht sogar ausschließlich über mobile Endgeräte wie Smartphones und Tablets erfolgen wird, stellt die Bayerische Staatsbibliothek gegenwärtig ihre Basisdienste ebenso wie ihre digitalen Content-Angebote sukzessive als mobile Applikationen bereit. Zuerst wurden der Online-Katalog und die Website der Bibliothek als generische, auf allen gängigen Smartphone-Browsern lauffähige, mobile Applikationen programmiert. In einem weiteren Schritt hat die Bayerische Staatsbibliothek 5o digitalisierte Spitzenstücke ihres Bestandes als native App »Famous Books -Treasures of the Bavarian State Library« für iPad und iPhone bereitgestellt, darauf folgte im Frühling 2011 die App »Islamic Books - Oriental treasures of the Bavarian State Library«. Aktuell experimentiert die Bayerische Staatsbibliothek zudem mit Augmented-Reality-Anwendungen. In einer mobilen Applikation »Ludwig II.« soll digitalisierter Bibliothekscontent zum berühmten bayerischen »Märchenkönig« georeferenziert an herausragenden Wirkungsstätten des Königs wie Schloss Neuschwanstein als Augmented-Reality-Applikation angeboten werden. Der Artikel stellt die verschiedenen mobilen Services und Anwendungen der Bayerischen Staatsbibliothek vor, beleuchtet ihre technische Realisierung und bewertet die Chancen und Grenzen bibliothekarischer Dienste im mobilen Internet.
  2. Kozak, M.; Iefremova, O.; Hartley, J.: Spamming in scholarly publishing : a case study (2016) 0.02
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    Abstract
    Spam has become an issue of concern in almost all areas where the Internet is involved, and many people today have become victims of spam from publishers and individual journals. We studied this phenomenon in the field of scholarly publishing from the perspective of a single author. We examined 1,024 such spam e-mails received by Marcin Kozak from publishers and journals over a period of 391 days, asking him to submit an article to their journal. We collected the following information: where the request came from; publishing model applied; fees charged; inclusion or not in the Directory of Open Access Journals (DOAJ); and presence or not in Beall's (2014) listing of dubious journals. Our research showed that most of the publishers that sent e-mails inviting manuscripts were (i) using the open access model, (ii) using article-processing charges to fund their journal's operations; (iii) offering very short peer-review times, (iv) on Beall's list, and (v) misrepresenting the location of their headquarters. Some years ago, a letter of invitation to submit an article to a particular journal was considered a kind of distinction. Today, e-mails inviting submissions are generally spam, something that misleads young researchers and irritates experienced ones.
  3. Nikolov, D.; Lalmas, M.; Flammini, A.; Menczer, F.: Quantifying biases in online information exposure (2019) 0.02
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    Abstract
    Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on online technologies such as search engines and social media may limit exposure to diverse points of view and make us vulnerable to manipulation by disinformation. In this article, we mine a massive data set of web traffic to quantify two kinds of bias: (i) homogeneity bias, which is the tendency to consume content from a narrow set of information sources, and (ii) popularity bias, which is the selective exposure to content from top sites. Our analysis reveals different bias levels across several widely used web platforms. Search exposes users to a diverse set of sources, while social media traffic tends to exhibit high popularity and homogeneity bias. When we focus our analysis on traffic to news sites, we find higher levels of popularity bias, with smaller differences across applications. Overall, our results quantify the extent to which our choices of online systems confine us inside "social bubbles."
  4. Schultz, S.: ¬Die eine App für alles : Mobile Zukunft in China (2016) 0.02
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    Date
    22. 6.2018 14:22:02
  5. Barrio, P.; Gravano, L.: Sampling strategies for information extraction over the deep web (2017) 0.02
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    Abstract
    Information extraction systems discover structured information in natural language text. Having information in structured form enables much richer querying and data mining than possible over the natural language text. However, information extraction is a computationally expensive task, and hence improving the efficiency of the extraction process over large text collections is of critical interest. In this paper, we focus on an especially valuable family of text collections, namely, the so-called deep-web text collections, whose contents are not crawlable and are only available via querying. Important steps for efficient information extraction over deep-web text collections (e.g., selecting the collections on which to focus the extraction effort, based on their contents; or learning which documents within these collections-and in which order-to process, based on their words and phrases) require having a representative document sample from each collection. These document samples have to be collected by querying the deep-web text collections, an expensive process that renders impractical the existing sampling approaches developed for other data scenarios. In this paper, we systematically study the space of query-based document sampling techniques for information extraction over the deep web. Specifically, we consider (i) alternative query execution schedules, which vary on how they account for the query effectiveness, and (ii) alternative document retrieval and processing schedules, which vary on how they distribute the extraction effort over documents. We report the results of the first large-scale experimental evaluation of sampling techniques for information extraction over the deep web. Our results show the merits and limitations of the alternative query execution and document retrieval and processing strategies, and provide a roadmap for addressing this critically important building block for efficient, scalable information extraction.
  6. Willkommen in der Datenwelt! : Haben wir unser digitales Leben noch im Griff? (2017) 0.02
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    Content
    Digital-Manifest (I): Digitale Demokratie statt Datendiktatur: Es droht die Automatisierung der Gesellschaft. (S.6) - Digital-Manifest (II): Eine Strategie für das digitale Zeitalter: Wie können wir unsere Demokratie schützen? Digital-Manifest: Expertenkommentare(S.15) - Die Debatte über mögliche Gefahren geht weiter. Essay: Was ist uns die Privatsphäre wert? (S.18) - Wer uneingeschränkt persönliche Informationen preisgibt, liefert sich aus. Datenschutz: Die Folgen der digitalen Transparenz (S.20) - Neuen Organisationsformen gehört die Zukunft. Epidemiologie: Eine Diagnose der Menschheit (S.28) - Mit einem Supercomputer stellen Forscher den globalen Gesundheitszustand fest. Maschinelles Lernen: Intelligenz bei Mensch und Computer (S.32) - Im Gegensatz zu uns lösen Algorithmen meist nur sehr spezielle Probleme - zumindest bislang. Ethik: Wir müssen autonome Killerroboter verbieten (S.40) - Maschinen überblicken nicht die Folgen ihres Tuns. Big und Smart Data: Zweckbindung zwecklos? (S.48) - Die Weiterverwendbarkeit von Daten stößt an Grenzen. Datensparsamkeit: Zukunftsfähig statt überholt (S.56) - Die Weiterverwendbarkeit von Daten stößt an Grenzen. Informationelle Selbstbestimmung: Ein erstrebenswertes Ziel (S.62) - Persönliche Entfaltung muss möglich bleiben. Digital Dienste: Zwischen Innovation und Sicherheit (S.68) - Schutz- und Kontrollbedarf fördert das Nutzervertrauen. Privatsphäre: Interview "Jede Äußerung wird konserviert" (S.74) - Sammelwut bedroht uns alle, meint Markus Beckedahl. (S.78)
  7. Landwehr, A.: China schafft digitales Punktesystem für den "besseren" Menschen (2018) 0.01
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    Date
    22. 6.2018 14:29:46
  8. Andrade, T.C.; Dodebei, V.: Traces of digitized newspapers and bom-digital news sites : a trail to the memory on the internet (2016) 0.01
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    Date
    19. 1.2019 17:42:22
  9. Social Media und Web Science : das Web als Lebensraum, Düsseldorf, 22. - 23. März 2012, Proceedings, hrsg. von Marlies Ockenfeld, Isabella Peters und Katrin Weller. DGI, Frankfurt am Main 2012 (2012) 0.01
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  10. Oguz, F.; Koehler, W.: URL decay at year 20 : a research note (2016) 0.01
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    Date
    22. 1.2016 14:37:14
  11. Hartmann, B.: Ab ins MoMA : zum virtuellen Museumsgang (2011) 0.01
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    Date
    3. 5.1997 8:44:22
  12. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011) 0.01
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    Date
    22. 1.2011 14:27:06
  13. Okoli, C.; Mehdi, M.; Mesgari, M.; Nielsen, F.A.; Lanamäki, A.: Wikipedia in the eyes of its beholders : a systematic review of scholarly research on Wikipedia readers and readership (2014) 0.01
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    Date
    18.11.2014 13:22:03
  14. Firnkes, M.: Schöne neue Welt : der Content der Zukunft wird von Algorithmen bestimmt (2015) 0.01
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    Date
    5. 7.2015 22:02:31
  15. Egbert, J.; Biber, D.; Davies, M.: Developing a bottom-up, user-based method of web register classification (2015) 0.01
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    Date
    4. 8.2015 19:22:04
  16. Evans, H.K.; Ovalle, J.; Green, S.: Rockin' robins : do congresswomen rule the roost in the Twittersphere? (2016) 0.01
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    Date
    22. 1.2016 11:51:19
  17. Arbelaitz, O.; Martínez-Otzeta. J.M.; Muguerza, J.: User modeling in a social network for cognitively disabled people (2016) 0.01
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    Date
    22. 1.2016 12:02:26
  18. Dufour, C.; Bartlett, J.C.; Toms, E.G.: Understanding how webcasts are used as sources of information (2011) 0.01
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    Date
    22. 1.2011 14:16:14
  19. Zimmer, M.; Proferes, N.J.: ¬A topology of Twitter research : disciplines, methods, and ethics (2014) 0.01
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    Date
    20. 1.2015 18:30:22
  20. Bhattacharya, S.; Yang, C.; Srinivasan, P.; Boynton, B.: Perceptions of presidential candidates' personalities in twitter (2016) 0.01
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    Date
    22. 1.2016 11:25:47