Search (131 results, page 5 of 7)

  • × theme_ss:"Automatisches Klassifizieren"
  1. 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
  2. Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.00 
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    Date
    22. 3.2009 19:11:54
  3. Zhu, W.Z.; Allen, R.B.: Document clustering using the LSI subspace signature model (2013) 0.00 
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    Date
    23. 3.2013 13:22:36
  4. 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
  5. Shafer, K.E.: Automatic Subject Assignment via the Scorpion System (2001) 0.00 
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    Source
    Journal of library administration. 34(2001) nos.1/2, S.187-189
  6. Prabowo, R.; Jackson, M.; Burden, P.; Knoell, H.-D.: Ontology-based automatic classification for the Web pages : design, implementation and evaluation (2002) 0.00 
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    Content
    Beitrag bei: The Third International Conference on Web Information Systems Engineering (WISE'00) Dec., 12-14, 2002, Singapore, S.182.
  7. Wu, M.; Liu, Y.-H.; Brownlee, R.; Zhang, X.: Evaluating utility and automatic classification of subject metadata from Research Data Australia (2021) 0.00 
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    Abstract
    In this paper, we present a case study of how well subject metadata (comprising headings from an international classification scheme) has been deployed in a national data catalogue, and how often data seekers use subject metadata when searching for data. Through an analysis of user search behaviour as recorded in search logs, we find evidence that users utilise the subject metadata for data discovery. Since approximately half of the records ingested by the catalogue did not include subject metadata at the time of harvest, we experimented with automatic subject classification approaches in order to enrich these records and to provide additional support for user search and data discovery. Our results show that automatic methods work well for well represented categories of subject metadata, and these categories tend to have features that can distinguish themselves from the other categories. Our findings raise implications for data catalogue providers; they should invest more effort to enhance the quality of data records by providing an adequate description of these records for under-represented subject categories.
  8. Chung, Y.M.; Lee, J.Y.: ¬A corpus-based approach to comparative evaluation of statistical term association measures (2001) 0.00 
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    Date
    29. 9.2001 14:01:18
  9. Ibekwe-SanJuan, F.; SanJuan, E.: From term variants to research topics (2002) 0.00 
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    Source
    Knowledge organization. 29(2002) nos.3/4, S.181-197
  10. Giorgetti, D.; Sebastiani, F.: Automating survey coding by multiclass text categorization techniques (2003) 0.00 
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    Date
    9. 7.2006 10:29:12
  11. Ma, Z.; Sun, A.; Cong, G.: On predicting the popularity of newly emerging hashtags in Twitter (2013) 0.00 
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    Date
    25. 6.2013 19:05:29
  12. Mengle, S.; Goharian, N.: Passage detection using text classification (2009) 0.00 
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    Date
    22. 3.2009 19:14:43
  13. Liu, R.-L.: ¬A passage extractor for classification of disease aspect information (2013) 0.00 
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    Date
    28.10.2013 19:22:57
  14. Na, J.-C.; Sui, H.; Khoo, C.; Chan, S.; Zhou, Y.: Effectiveness of simple linguistic processing in automatic sentiment classification of product reviews (2004) 0.00 
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    Source
    Knowledge organization and the global information society: Proceedings of the 8th International ISKO Conference 13-16 July 2004, London, UK. Ed.: I.C. McIlwaine
  15. Khoo, C.S.G.; Ou, S.: Machine versus human clustering of concepts across documents (2008) 0.00 
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    Culture and identity in knowledge organization: Proceedings of the Tenth International ISKO Conference 5-8 August 2008, Montreal, Canada. Ed. by Clément Arsenault and Joseph T. Tennis
  16. Wartena, C.; Sommer, M.: Automatic classification of scientific records using the German Subject Heading Authority File (SWD) (2012) 0.00 
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    Proceedings of the 2nd International Workshop on Semantic Digital Archives held in conjunction with the 16th Int. Conference on Theory and Practice of Digital Libraries (TPDL) on September 27, 2012 in Paphos, Cyprus [http://ceur-ws.org/Vol-912/proceedings.pdf]. Eds.: A. Mitschik et al
  17. Barthel, S.; Tönnies, S.; Balke, W.-T.: Large-scale experiments for mathematical document classification (2013) 0.00 
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    Source
    15th International Conference on Asia-Pacific Digital Libraries ICADL 2013. Bangalore, India. [to appear, 2013]
  18. Sebastiani, F.: Machine learning in automated text categorization (2002) 0.00 
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    Source
    ACM computing surveys. 34(2002) no.1, S.1-47
  19. Koch, T.; Ardö, A.: Automatic classification of full-text HTML-documents from one specific subject area : DESIRE II D3.6a, Working Paper 2 (2000) 0.00 
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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.
  20. Guerrero-Bote, V.P.; Moya Anegón, F. de; Herrero Solana, V.: Document organization using Kohonen's algorithm (2002) 0.00 
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    Source
    Information processing and management. 38(2002) no.1, S.79-89

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