Search (43 results, page 1 of 3)

  • × theme_ss:"Visualisierung"
  1. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.02
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  2. Thissen, F.: Screen-Design-Handbuch : Effektiv informieren und kommunizieren mit Multimedia (2001) 0.02
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    Classification
    TYH (FH K)
    Date
    22. 3.2008 14:35:21
    GHBS
    TYH (FH K)
  3. Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016) 0.01
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    Date
    20. 1.2015 18:30:22
  4. Teutsch, K.: ¬Die Welt ist doch eine Scheibe : Google-Herausforderer eyePlorer (2009) 0.01
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    Content
    Skelett mit Sonnenbrille Hirsch sitzt in einem grell erleuchteten Konferenzraum. In der rechten Ecke steht ein Skelett, dem jemand eine Sonnenbrille aufgeklemmt hat. In der Hand hält Hirsch ein Modellgehirn, auf dem er im Rhythmus seines Sprachflusses mit den Fingern trommelt. Obwohl im Verlauf der nächsten Stunden erschreckend verwickelte Netzdiagramme zum Einsatz kommen, hält Hirsch sich an die Suggestivkraft des Bildes. Er sagt: "Das Primärerlebnis der Maschine ist bei Google das eines Jägers. Sie pirscht sich an eine Internetseite heran." Man denkt: "Genauso fühlt es sich an: Suchbegriff eingeben, 'enter' drücken, Website schießen!", schon kommt die Komplementärmetapher geschmeidig aus dem Köcher: Im Gegensatz zum Google-Jäger, sagt Hirsch, sei der eyePlorer ein Sammler, der stöbere, organisiere und dann von allem nasche. Hier werden Informationen, auf die handelsübliche Suchmaschinen nur verweisen, kulinarisch aufbereitet und zu Schwerpunkten verknüpft. Im Gegensatz zu ihren Vorgängern ist die Maschine ansatzweise intelligent. Sie findet im Laufe einer Sitzung heraus, worum es dem Benutzer geht, versteht den Zusammenhang von Suche und Inhalt und ist deshalb in der Lage, Empfehlungen auszusprechen.
  5. Schek, M.: Automatische Klassifizierung in Erschließung und Recherche eines Pressearchivs (2006) 0.01
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    Abstract
    Die Süddeutsche Zeitung (SZ) verfügt seit ihrer Gründung 1945 über ein Pressearchiv, das die Texte der eigenen Redakteure und zahlreicher nationaler und internationaler Publikationen dokumentiert und für Recherchezwecke bereitstellt. Die DIZ-Pressedatenbank (www.medienport.de) ermöglicht die browserbasierte Recherche für Redakteure und externe Kunden im Intra- und Internet und die kundenspezifischen Content Feeds für Verlage, Rundfunkanstalten und Portale. Die DIZ-Pressedatenbank enthält z. Zt. 7,8 Millionen Artikel, die jeweils als HTML oder PDF abrufbar sind. Täglich kommen ca. 3.500 Artikel hinzu, von denen ca. 1.000 durch Dokumentare inhaltlich erschlossen werden. Die Informationserschließung erfolgt im DIZ nicht durch die Vergabe von Schlagwörtern am Dokument, sondern durch die Verlinkung der Artikel mit "virtuellen Mappen", den Dossiers. Insgesamt enthält die DIZ-Pressedatenbank ca. 90.000 Dossiers, die untereinander zum "DIZ-Wissensnetz" verlinkt sind. DIZ definiert das Wissensnetz als Alleinstellungsmerkmal und wendet beträchtliche personelle Ressourcen für die Aktualisierung und Qualitätssicherung der Dossiers auf. Im Zuge der Medienkrise mussten sich DIZ der Herausforderung stellen, bei sinkenden Lektoratskapazitäten die Qualität der Informationserschließung im Input zu erhalten. Auf der Outputseite gilt es, eine anspruchsvolle Zielgruppe - u.a. die Redakteure der Süddeutschen Zeitung - passgenau und zeitnah mit den Informationen zu versorgen, die sie für ihre tägliche Arbeit benötigt. Bezogen auf die Ausgangssituation in der Dokumentation der Süddeutschen Zeitung identifizierte DIZ drei Ansatzpunkte, wie die Aufwände auf der Inputseite (Lektorat) zu optimieren sind und gleichzeitig auf der Outputseite (Recherche) das Wissensnetz besser zu vermarkten ist: - (Teil-)Automatische Klassifizierung von Pressetexten (Vorschlagwesen) - Visualisierung des Wissensnetzes - Neue Retrievalmöglichkeiten (Ähnlichkeitssuche, Clustering) Im Bereich "Visualisierung" setzt DIZ auf den Net-Navigator von intelligent views, eine interaktive Visualisierung allgemeiner Graphen, basierend auf einem physikalischen Modell. In den Bereichen automatische Klassifizierung, Ähnlichkeitssuche und Clustering hat DIZ sich für das Produkt nextBot der Firma Brainbot entschieden.
  6. Singh, A.; Sinha, U.; Sharma, D.k.: Semantic Web and data visualization (2020) 0.01
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    Abstract
    With the terrific growth of data volume and data being produced every second on millions of devices across the globe, there is a desperate need to manage the unstructured data available on web pages efficiently. Semantic Web or also known as Web of Trust structures the scattered data on the Internet according to the needs of the user. It is an extension of the World Wide Web (WWW) which focuses on manipulating web data on behalf of Humans. Due to the ability of the Semantic Web to integrate data from disparate sources and hence makes it more user-friendly, it is an emerging trend. Tim Berners-Lee first introduced the term Semantic Web and since then it has come a long way to become a more intelligent and intuitive web. Data Visualization plays an essential role in explaining complex concepts in a universal manner through pictorial representation, and the Semantic Web helps in broadening the potential of Data Visualization and thus making it an appropriate combination. The objective of this chapter is to provide fundamental insights concerning the semantic web technologies and in addition to that it also elucidates the issues as well as the solutions regarding the semantic web. The purpose of this chapter is to highlight the semantic web architecture in detail while also comparing it with the traditional search system. It classifies the semantic web architecture into three major pillars i.e. RDF, Ontology, and XML. Moreover, it describes different semantic web tools used in the framework and technology. It attempts to illustrate different approaches of the semantic web search engines. Besides stating numerous challenges faced by the semantic web it also illustrates the solutions.
  7. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.01
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    Date
    30. 5.2010 16:22:35
  8. Platis, N. et al.: Visualization of uncertainty in tag clouds (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  9. Trunk, D.: Semantische Netze in Informationssystemen : Verbesserung der Suche durch Interaktion und Visualisierung (2005) 0.00
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    Date
    30. 1.2007 18:22:41
  10. Kocijan, K.: Visualizing natural language resources (2015) 0.00
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  11. Palm, F.: QVIZ : Query and context based visualization of time-spatial cultural dynamics (2007) 0.00
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    Content
    Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".
  12. Osinska, V.; Bala, P.: New methods for visualization and improvement of classification schemes : the case of computer science (2010) 0.00
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    Date
    22. 7.2010 19:36:46
  13. Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013) 0.00
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    Date
    4. 2.2015 9:22:39
  14. Pfeffer, M.; Eckert, K.; Stuckenschmidt, H.: Visual analysis of classification systems and library collections (2008) 0.00
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  15. Eckert, K: ¬The ICE-map visualization (2011) 0.00
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  16. Thissen, F.: Screen-Design-Manual : Communicating Effectively Through Multimedia (2003) 0.00
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    Date
    22. 3.2008 14:29:25
  17. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.00
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    Date
    22. 7.2006 16:11:05
  18. Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018) 0.00
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