Search (83 results, page 2 of 5)

  • × theme_ss:"Automatisches Klassifizieren"
  1. Bock, H.-H.: Automatische Klassifikation : theoretische und praktische Methoden zur Gruppierung und Strukturierung von Daten (Cluster-Analyse) (1974) 0.01 
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  2. Kleinoeder, H.H.; Puzicha, J.: Automatische Katalogisierung am Beispiel einer Pilotanwendung (2002) 0.01 
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  3. 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
  4. GERHARD : eine Spezialsuchmaschine für die Wissenschaft (1998) 0.01 
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  5. Ardö, A.; Koch, T.: Automatic classification applied to full-text Internet documents in a robot-generated subject index (1999) 0.01 
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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. Liu, R.-L.: Context-based term frequency assessment for text classification (2010) 0.00 
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    Abstract
    Automatic text classification (TC) is essential for the management of information. To properly classify a document d, it is essential to identify the semantics of each term t in d, while the semantics heavily depend on context (neighboring terms) of t in d. Therefore, we present a technique CTFA (Context-based Term Frequency Assessment) that improves text classifiers by considering term contexts in test documents. The results of the term context recognition are used to assess term frequencies of terms, and hence CTFA may easily work with various kinds of text classifiers that base their TC decisions on term frequencies, without needing to modify the classifiers. Moreover, CTFA is efficient, and neither huge memory nor domain-specific knowledge is required. Empirical results show that CTFA successfully enhances performance of several kinds of text classifiers on different experimental data.
  7. Wätjen, H.-J.; Diekmann, B.; Möller, G.; Carstensen, K.-U.: Bericht zum DFG-Projekt: GERHARD : German Harvest Automated Retrieval and Directory (1998) 0.00 
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  8. Wätjen, H.-J.: Automatisches Sammeln, Klassifizieren und Indexieren von wissenschaftlich relevanten Informationsressourcen im deutschen World Wide Web : das DFG-Projekt GERHARD (1998) 0.00 
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  9. Vizine-Goetz, D.: NetLab / OCLC collaboration seeks to improve Web searching (1999) 0.00 
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  10. Möller, G.: Automatic classification of the World Wide Web using Universal Decimal Classification (1999) 0.00 
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    Source
    Online information 99: 23rd International Online Information Meeting, Proceedings, London, 7-9 December 1999. Ed.: D. Raitt et al
  11. Braun, T.: Dokumentklassifikation durch Clustering (o.J.) 0.00 
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  12. Shen, D.; Chen, Z.; Yang, Q.; Zeng, H.J.; Zhang, B.; Lu, Y.; Ma, W.Y.: Web page classification through summarization (2004) 0.00 
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  13. Golub, K.; Soergel, D.; Buchanan, G.; Tudhope, D.; Lykke, M.; Hiom, D.: ¬A framework for evaluating automatic indexing or classification in the context of retrieval (2016) 0.00 
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  14. Dolin, R.; Agrawal, D.; El Abbadi, A.; Pearlman, J.: Using automated classification for summarizing and selecting heterogeneous information sources (1998) 0.00 
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    Source
    D-Lib magazine. 4(1998) no.1
  15. Hagedorn, K.; Chapman, S.; Newman, D.: Enhancing search and browse using automated clustering of subject metadata (2007) 0.00 
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    Source
    D-Lib magazine. 13(2007) nos.7/8, x S
  16. Panyr, J.: Vektorraum-Modell und Clusteranalyse in Information-Retrieval-Systemen (1987) 0.00 
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  17. Savic, D.: Designing an expert system for classifying office documents (1994) 0.00 
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  18. Fangmeyer, H.; Gloden, R.: Bewertung und Vergleich von Klassifikationsergebnissen bei automatischen Verfahren (1978) 0.00 
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  19. Bollmann, P.; Konrad, E.; Schneider, H.-J.; Zuse, H.: Anwendung automatischer Klassifikationsverfahren mit dem System FAKYR (1978) 0.00 
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  20. Schulze, U.: Erfahrungen bei der Anwendung automatischer Klassifizierungsverfahren zur Inhaltsanalyse einer Dokumentenmenge (1978) 0.00 
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