Search (27 results, page 1 of 2)

  • × theme_ss:"Automatisches Klassifizieren"
  • × year_i:[2000 TO 2010}
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.15 
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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
    Source
    Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 1-4 November 2004, Brighton, UK
  2. Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.07 
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    Date
    5. 5.2003 14:17:22
    Source
    Journal of library administration. 34(2001) nos.3/4, S.221-228
  3. Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007) 0.04 
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    Date
    22. 9.2008 18:31:54
    Source
    International cataloguing and bibliographic control. 36(2007) no.4, S.78-82
  4. Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.03 
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    Date
    22. 3.2009 19:11:54
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.803-813
  5. Mengle, S.; Goharian, N.: Passage detection using text classification (2009) 0.03 
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    Date
    22. 3.2009 19:14:43
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.814-825
  6. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.02 
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    Date
    22. 8.2009 12:54:24
  7. Fong, A.C.M.: Mining a Web citation database for document clustering (2002) 0.01 
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    Source
    Applied artificial intelligence. 16(2002) no.4, S.283-292
  8. Major, R.L.; Ragsdale, C.T.: ¬An aggregation approach to the classification problem using multiple prediction experts (2000) 0.01 
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    Source
    Information processing and management. 36(2000) no.4, S.683-696
  9. Automatic classification research at OCLC (2002) 0.01 
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    Date
    5. 5.2003 9:22:09
  10. 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
  11. Shafer, K.E.: Evaluating Scorpion Results (2001) 0.01 
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    Source
    Journal of library administration. 34(2001) nos.3/4, S.237-244
  12. Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009) 0.01 
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    Date
    22. 8.2009 19:51:28
  13. Koch, T.; Ardö, A.: Automatic classification of full-text HTML-documents from one specific subject area : DESIRE II D3.6a, Working Paper 2 (2000) 0.01 
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    Content
    1 Introduction / 2 Method overview / 3 Ei thesaurus preprocessing / 4 Automatic classification process: 4.1 Matching -- 4.2 Weighting -- 4.3 Preparation for display / 5 Results of the classification process / 6 Evaluations / 7 Software / 8 Other applications / 9 Experiments with universal classification systems / References / Appendix A: Ei classification service: Software / Appendix B: Use of the classification software as subject filter in a WWW harvester.
  14. Walther, R.: Möglichkeiten und Grenzen automatischer Klassifikationen von Web-Dokumenten (2001) 0.01 
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    Date
    4. 5.2003 19:55:46
  15. Schek, M.: Automatische Klassifizierung und Visualisierung im Archiv der Süddeutschen Zeitung (2005) 0.01 
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    Abstract
    DIZ definiert das Wissensnetz als Alleinstellungsmerkmal und wendet beträchtliche personelle Ressourcen für die Aktualisierung und Oualitätssicherung der Dossiers auf. Nach der Umstellung auf den komplett digitalisierten Workflow im April 2001 identifizierte DIZ vier Ansatzpunkte, wie die Aufwände auf der Inputseite (Lektorat) zu optimieren sind und gleichzeitig auf der Outputseite (Recherche) das Wissensnetz besser zu vermarkten ist: 1. (Teil-)Automatische Klassifizierung von Pressetexten (Vorschlagwesen) 2. Visualisierung des Wissensnetzes (Topic Mapping) 3. (Voll-)Automatische Klassifizierung und Optimierung des Wissensnetzes 4. Neue Retrievalmöglichkeiten (Clustering, Konzeptsuche) Die Projekte 1 und 2 "Automatische Klassifizierung und Visualisierung" starteten zuerst und wurden beschleunigt durch zwei Entwicklungen: - Der Bayerische Rundfunk (BR), ursprünglich Mitbegründer und 50%-Gesellschafter der DIZ München GmbH, entschloss sich aus strategischen Gründen, zum Ende 2003 aus der Kooperation auszusteigen. - Die Medienkrise, hervorgerufen durch den massiven Rückgang der Anzeigenerlöse, erforderte auch im Süddeutschen Verlag massive Einsparungen und die Suche nach neuen Erlösquellen. Beides führte dazu, dass die Kapazitäten im Bereich Pressedokumentation von ursprünglich rund 20 (nur SZ, ohne BR-Anteil) auf rund 13 zum 1. Januar 2004 sanken und gleichzeitig die Aufwände für die Pflege des Wissensnetzes unter verstärkten Rechtfertigungsdruck gerieten. Für die Projekte 1 und 2 ergaben sich daraus drei quantitative und qualitative Ziele: - Produktivitätssteigerung im Lektorat - Konsistenzverbesserung im Lektorat - Bessere Vermarktung und intensivere Nutzung der Dossiers in der Recherche Alle drei genannten Ziele konnten erreicht werden, wobei insbesondere die Produktivität im Lektorat gestiegen ist. Die Projekte 1 und 2 "Automatische Klassifizierung und Visualisierung" sind seit Anfang 2004 erfolgreich abgeschlossen. Die Folgeprojekte 3 und 4 laufen seit Mitte 2004 und sollen bis Mitte 2005 abgeschlossen sein. Im folgenden wird in Abschnitt 2 die Produktauswahl und Arbeitsweise der Automatischen Klassifizierung beschrieben. Abschnitt 3 schildert den Einsatz der Wissensnetz-Visualisierung in Lektorat und Recherche. Abschnitt 4 fasst die Ergebnisse der Projekte 1 und 2 zusammen und gibt einen Ausblick auf die Ziele der Projekte 3 und 4.
  16. Hu, G.; Zhou, S.; Guan, J.; Hu, X.: Towards effective document clustering : a constrained K-means based approach (2008) 0.01 
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    Source
    Information processing and management. 44(2008) no.4, S.1397-1409
  17. Khoo, C.S.G.; Ng, K.; Ou, S.: ¬An exploratory study of human clustering of Web pages (2003) 0.01 
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    Date
    12. 9.2004 9:56:22
  18. Reiner, U.: Automatische DDC-Klassifizierung bibliografischer Titeldatensätze der Deutschen Nationalbibliografie (2009) 0.01 
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