Search (42 results, page 1 of 3)

  • × theme_ss:"Automatisches Klassifizieren"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.12 
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  2. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.05 
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    Date
    22. 8.2009 12:54:24
    Theme
    Klassifikationssysteme im Online-Retrieval
  3. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.03 
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    Date
    1. 8.1996 22:08:06
    Theme
    Klassifikationssysteme im Online-Retrieval
  4. Möller, G.: Automatic classification of the World Wide Web using Universal Decimal Classification (1999) 0.02 
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    Source
    Online information 99: 23rd International Online Information Meeting, Proceedings, London, 7-9 December 1999. Ed.: D. Raitt et al
    Theme
    Klassifikationssysteme im Online-Retrieval
  5. Ardö, A.; Koch, T.: Automatic classification applied to full-text Internet documents in a robot-generated subject index (1999) 0.02 
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    Source
    Online information 99: 23rd International Online Information Meeting, Proceedings, London, 7-9 December 1999. Ed.: D. Raitt et al
  6. Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.02 
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    Date
    5. 5.2003 14:17:22
  7. Wätjen, H.-J.: Automatisches Sammeln, Klassifizieren und Indexieren von wissenschaftlich relevanten Informationsressourcen im deutschen World Wide Web : das DFG-Projekt GERHARD (1998) 0.02 
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    Footnote
    Vortrag auf der 20. Online-Tagung der Deutschen Gesellschaft für Dokumentation, 5.-7.5.1998. Session 3: WWW-Suchmaschinen
    Theme
    Klassifikationssysteme im Online-Retrieval
  8. HaCohen-Kerner, Y. et al.: Classification using various machine learning methods and combinations of key-phrases and visual features (2016) 0.01 
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    Date
    1. 2.2016 18:25:22
  9. GERHARD : eine Spezialsuchmaschine für die Wissenschaft (1998) 0.01 
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    Theme
    Klassifikationssysteme im Online-Retrieval
  10. Wätjen, H.-J.; Diekmann, B.; Möller, G.; Carstensen, K.-U.: Bericht zum DFG-Projekt: GERHARD : German Harvest Automated Retrieval and Directory (1998) 0.01 
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    Theme
    Klassifikationssysteme im Online-Retrieval
  11. Vizine-Goetz, D.: NetLab / OCLC collaboration seeks to improve Web searching (1999) 0.01 
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    Theme
    Klassifikationssysteme im Online-Retrieval
  12. Oberhauser, O.: Automatisches Klassifizieren und Bibliothekskataloge (2005) 0.01 
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    Abstract
    In der bibliothekarischen Welt sind die Vorzüge einer klassifikatorischen Inhaltserschließung seit jeher wohlbekannt. Auch im Zeitalter der Online-Kataloge gibt es dafür keinen wirklichen Ersatz, da - kurz formuliert - ein stichwortbasiertes Retrieval alleine mit Problemen wie Ambiguität und Mehrsprachigkeit nicht fertig zu werden vermag. Zahlreiche Online-Kataloge weisen daher Notationen verschiedener Klassifikationssysteme auf; allerdings sind die darauf basierenden Abfragemöglichkeiten meist noch arg unterentwickelt. Viele Datensätze in OPACs sind aber überhaupt nicht sachlich erschlossen, sei es, dass sie aus retrospektiv konvertierten Nominalkatalogen stammen, sei es, dass ein Mangel an personellen Ressourcen ihre inhaltliche Erschließung verhindert hat. Angesichts großer Mengen solcher Datensätze liegt ein Interesse an automatischen Verfahren zur Sacherschließung durchaus nahe.
  13. Bock, H.-H.: Datenanalyse zur Strukturierung und Ordnung von Information (1989) 0.01 
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    Pages
    S.1-22
  14. Dubin, D.: Dimensions and discriminability (1998) 0.01 
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    Date
    22. 9.1997 19:16:05
  15. Automatic classification research at OCLC (2002) 0.01 
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    Date
    5. 5.2003 9:22:09
  16. Yoon, Y.; Lee, C.; Lee, G.G.: ¬An effective procedure for constructing a hierarchical text classification system (2006) 0.01 
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    Date
    22. 7.2006 16:24:52
  17. Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007) 0.01 
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    Date
    22. 9.2008 18:31:54
  18. Leroy, G.; Miller, T.; Rosemblat, G.; Browne, A.: ¬A balanced approach to health information evaluation : a vocabulary-based naïve Bayes classifier and readability formulas (2008) 0.01 
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    Abstract
    Since millions seek health information online, it is vital for this information to be comprehensible. Most studies use readability formulas, which ignore vocabulary, and conclude that online health information is too difficult. We developed a vocabularly-based, naïve Bayes classifier to distinguish between three difficulty levels in text. It proved 98% accurate in a 250-document evaluation. We compared our classifier with readability formulas for 90 new documents with different origins and asked representative human evaluators, an expert and a consumer, to judge each document. Average readability grade levels for educational and commercial pages was 10th grade or higher, too difficult according to current literature. In contrast, the classifier showed that 70-90% of these pages were written at an intermediate, appropriate level indicating that vocabulary usage is frequently appropriate in text considered too difficult by readability formula evaluations. The expert considered the pages more difficult for a consumer than the consumer did.
  19. Koch, T.: Nutzung von Klassifikationssystemen zur verbesserten Beschreibung, Organisation und Suche von Internetressourcen (1998) 0.01 
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    Theme
    Klassifikationssysteme im Online-Retrieval
  20. Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.01 
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    Date
    22. 3.2009 19:11:54

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