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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) 0.22
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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. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.03
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    Abstract
    The Wolverhampton Web Library (WWLib) is a WWW search engine that provides access to UK based information. The experimental version developed in 1995, was a success but highlighted the need for a much higher degree of automation. An interesting feature of the experimental WWLib was that it organised information according to DDC. Discusses the advantages of classification and describes the automatic classifier that is being developed in Java as part of the new, fully automated WWLib
    Date
    1. 8.1996 22:08:06
  3. Classification, automation, and new media : Proceedings of the 24th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Passau, March 15 - 17, 2000 (2002) 0.02
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    Abstract
    Given the huge amount of information in the internet and in practically every domain of knowledge that we are facing today, knowledge discovery calls for automation. The book deals with methods from classification and data analysis that respond effectively to this rapidly growing challenge. The interested reader will find new methodological insights as well as applications in economics, management science, finance, and marketing, and in pattern recognition, biology, health, and archaeology.
    Content
    Data Analysis, Statistics, and Classification.- Pattern Recognition and Automation.- Data Mining, Information Processing, and Automation.- New Media, Web Mining, and Automation.- Applications in Management Science, Finance, and Marketing.- Applications in Medicine, Biology, Archaeology, and Others.- Author Index.- Subject Index.
  4. Yao, H.; Etzkorn, L.H.; Virani, S.: Automated classification and retrieval of reusable software components (2008) 0.01
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    Abstract
    The authors describe their research which improves software reuse by using an automated approach to semantically search for and retrieve reusable software components in large software component repositories and on the World Wide Web (WWW). Using automation and smart (semantic) techniques, their approach speeds up the search and retrieval of reusable software components, while retaining good accuracy, and therefore improves the affordability of software reuse. A program understanding of software components and natural language understanding of user queries was employed. Then the software component descriptions were compared by matching the resulting semantic representations of the user queries to the semantic representations of the software components to search for software components that best match the user queries. A proof of concept system was developed to test the authors' approach. The results of this proof of concept system were compared to human experts, and statistical analysis was performed on the collected experimental data. The results from these experiments demonstrate that this automated semantic-based approach for software reusable component classification and retrieval is successful when compared to the labor-intensive results from the experts, thus showing that this approach can significantly benefit software reuse classification and retrieval.
  5. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.01
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    Date
    22. 8.2009 12:54:24
    Language
    d
  6. Bock, H.-H.: Datenanalyse zur Strukturierung und Ordnung von Information (1989) 0.01
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    Language
    d
    Pages
    S.1-22
  7. Dubin, D.: Dimensions and discriminability (1998) 0.01
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    Date
    22. 9.1997 19:16:05
  8. Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009) 0.00
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    Date
    22. 8.2009 19:51:28
    Language
    d
  9. Egbert, J.; Biber, D.; Davies, M.: Developing a bottom-up, user-based method of web register classification (2015) 0.00
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    Date
    4. 8.2015 19:22:04
  10. Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.00
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    Date
    5. 5.2003 14:17:22
  11. HaCohen-Kerner, Y. et al.: Classification using various machine learning methods and combinations of key-phrases and visual features (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  12. Reiner, U.: Automatische DDC-Klassifizierung bibliografischer Titeldatensätze der Deutschen Nationalbibliografie (2009) 0.00
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    Date
    22. 1.2010 14:41:24
    Language
    d
  13. Automatic classification research at OCLC (2002) 0.00
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    Date
    5. 5.2003 9:22:09
  14. 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
  15. 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
  16. Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.00
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Years

Languages

  • d 45
  • e 40

Types

  • a 61
  • el 15
  • x 9
  • m 4
  • r 3
  • d 1
  • s 1
  • More… Less…