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  • × theme_ss:"Automatisches Klassifizieren"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.16 
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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. Piros, A.: Automatic interpretation of complex UDC numbers : towards support for library systems (2015) 0.03 
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    Abstract
    Analytico-synthetic and faceted classifications, such as Universal Decimal Classification (UDC) express content of documents with complex, pre-combined classification codes. Without classification authority control that would help manage and access structured notations, the use of UDC codes in searching and browsing is limited. Existing UDC parsing solutions are usually created for a particular database system or a specific task and are not widely applicable. The approach described in this paper provides a solution by which the analysis and interpretation of UDC notations would be stored into an intermediate format (in this case, in XML) by automatic means without any data or information loss. Due to its richness, the output file can be converted into different formats, such as standard mark-up and data exchange formats or simple lists of the recommended entry points of a UDC number. The program can also be used to create authority records containing complex UDC numbers which can be comprehensively analysed in order to be retrieved effectively. The Java program, as well as the corresponding schema definition it employs, is under continuous development. The current version of the interpreter software is now available online for testing purposes at the following web site: http://interpreter-eto.rhcloud.com. The future plan is to implement conversion methods for standard formats and to create standard online interfaces in order to make it possible to use the features of software as a service. This would result in the algorithm being able to be employed both in existing and future library systems to analyse UDC numbers without any significant programming effort.
    Source
    Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro
  3. Panyr, J.: STEINADLER: ein Verfahren zur automatischen Deskribierung und zur automatischen thematischen Klassifikation (1978) 0.01 
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    Source
    Nachrichten für Dokumentation. 29(1978), S.92-96
  4. Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.01 
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    Date
    5. 5.2003 14:17:22
  5. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.01 
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    Date
    22. 8.2009 12:54:24
  6. 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
  7. Savic, D.: Designing an expert system for classifying office documents (1994) 0.00 
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    Source
    Records management quarterly. 28(1994) no.3, S.20-29
  8. Savic, D.: Automatic classification of office documents : review of available methods and techniques (1995) 0.00 
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    Source
    Records management quarterly. 29(1995) no.4, S.3-18
  9. Ruocco, A.S.; Frieder, O.: Clustering and classification of large document bases in a parallel environment (1997) 0.00 
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    Date
    29. 7.1998 17:45:02
  10. Ruiz, M.E.; Srinivasan, P.: Combining machine learning and hierarchical indexing structures for text categorization (2001) 0.00 
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    Date
    11. 5.2003 18:29:44
  11. Bock, H.-H.: Datenanalyse zur Strukturierung und Ordnung von Information (1989) 0.00 
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    Pages
    S.1-22
  12. Dubin, D.: Dimensions and discriminability (1998) 0.00 
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    Date
    22. 9.1997 19:16:05
  13. Automatic classification research at OCLC (2002) 0.00 
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    Date
    5. 5.2003 9:22:09
  14. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.00 
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    Date
    1. 8.1996 22:08:06
  15. Yoon, Y.; Lee, C.; Lee, G.G.: ¬An effective procedure for constructing a hierarchical text classification system (2006) 0.00 
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    Date
    22. 7.2006 16:24:52
  16. Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007) 0.00 
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    Date
    22. 9.2008 18:31:54
  17. Drori, O.; Alon, N.: Using document classification for displaying search results (2003) 0.00 
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    Source
    Journal of information science. 29(2003) no.2, S.97-106
  18. Chung, Y.-M.; Noh, Y.-H.: Developing a specialized directory system by automatically classifying Web documents (2003) 0.00 
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    Source
    Journal of information science. 29(2003) no.2, S.117-126
  19. Liu, X.; Yu, S.; Janssens, F.; Glänzel, W.; Moreau, Y.; Moor, B.de: Weighted hybrid clustering by combining text mining and bibliometrics on a large-scale journal database (2010) 0.00 
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    Date
    1. 6.2010 9:29:57
  20. Li, T.; Zhu, S.; Ogihara, M.: Hierarchical document classification using automatically generated hierarchy (2007) 0.00 
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    Source
    Journal of intelligent information systems. 29(2007) no.2, S.211-230

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