Search (178 results, page 2 of 9)

  • × theme_ss:"Automatisches Klassifizieren"
  1. Kwok, K.L.: ¬The use of titles and cited titles as document representations for automatic classification (1975) 0.00 
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  2. Schiminovich, S.: Automatic classification and retrieval of documents by means of a bibliographic pattern discovery algorithm (1971) 0.00 
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  3. Wu, M.; Fuller, M.; Wilkinson, R.: Using clustering and classification approaches in interactive retrieval (2001) 0.00 
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  4. Fong, A.C.M.: Mining a Web citation database for document clustering (2002) 0.00 
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  5. May, A.D.: Automatic classification of e-mail messages by message type (1997) 0.00 
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    Abstract
    This article describes a system that automatically classifies e-mail messages in the HUMANIST electronic discussion group into one of 4 classes: questions, responses, announcement or administartive. A total of 1.372 messages were analyzed. The automatic classification of a message was based on string matching between a message text and predefined string sets for each of the massage types. The system's automated ability to accurately classify a message was compared against manually assigned codes. The Cohen's Kappa of .55 suggested that there was a statistical agreement between the automatic and manually assigned codes
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  6. Major, R.L.; Ragsdale, C.T.: ¬An aggregation approach to the classification problem using multiple prediction experts (2000) 0.00 
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  7. Ardö, A.; Koch, T.: Automatic classification applied to full-text Internet documents in a robot-generated subject index (1999) 0.00 
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  8. Chan, L.M.; Lin, X.; Zeng, M.L.: Structural and multilingual approaches to subject access on the Web (2000) 0.00 
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  9. Shafer, K.E.: Automatic Subject Assignment via the Scorpion System (2001) 0.00 
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  10. Yu, W.; Gong, Y.: Document clustering by concept factorization (2004) 0.00 
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  11. Reiner, U.: Automatic analysis of DDC notations (2007) 0.00 
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  12. Cortez, E.; Herrera, M.R.; Silva, A.S. da; Moura, E.S. de; Neubert, M.: Lightweight methods for large-scale product categorization (2011) 0.00 
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    Abstract
    In this article, we present a study about classification methods for large-scale categorization of product offers on e-shopping web sites. We present a study about the performance of previously proposed approaches and deployed a probabilistic approach to model the classification problem. We also studied an alternative way of modeling information about the description of product offers and investigated the usage of price and store of product offers as features adopted in the classification process. Our experiments used two collections of over a million product offers previously categorized by human editors and taxonomies of hundreds of categories from a real e-shopping web site. In these experiments, our method achieved an improvement of up to 9% in the quality of the categorization in comparison with the best baseline we have found.
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  13. Autonomy, Inc.: Automatic classification (o.J.) 0.00 
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    Abstract
    Autonomy's Classification solutions remove the necessity for organizations to rely on human intervention or manual processing of information, such as manual tagging, typically required to make most other e-business applications work. Autonomy's ability to consistently and accurately classify data automatically is a unique infrastructure solution that overcomes the predicaments surrounding the exponential growth of unstructured data.
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  14. Lindholm, J.; Schönthal, T.; Jansson , K.: Experiences of harvesting Web resources in engineering using automatic classification (2003) 0.00 
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    Abstract
    Authors describe the background and the work involved in setting up Engine-e, a Web index that uses automatic classification as a mean for the selection of resources in Engineering. Considerations in offering a robot-generated Web index as a successor to a manually indexed quality-controlled subject gateway are also discussed
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  15. Teich, E.; Degaetano-Ortlieb, S.; Fankhauser, P.; Kermes, H.; Lapshinova-Koltunski, E.: ¬The linguistic construal of disciplinarity : a data-mining approach using register features (2016) 0.00 
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  16. McKiernan, G.: Automated categorisation of Web resources : a profile of selected projects, research, products, and services (1996) 0.00 
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  17. Vizine-Goetz, D.: NetLab / OCLC collaboration seeks to improve Web searching (1999) 0.00 
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  18. Möller, G.: Automatic classification of the World Wide Web using Universal Decimal Classification (1999) 0.00 
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  19. Subramanian, S.; Shafer, K.E.: Clustering (1998) 0.00 
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  20. Shafer, K.E.: Evaluating Scorpion results (1998) 0.00 
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