Search (5 results, page 1 of 1)

  • × theme_ss:"Automatisches Klassifizieren"
  • × year_i:[1990 TO 2000}
  1. Koch, T.; Vizine-Goetz, D.: Automatic classification and content navigation support for Web services : DESIRE II cooperates with OCLC (1998) 0.04
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    Abstract
    Emerging standards in knowledge representation and organization are preparing the way for distributed vocabulary support in Internet search services. NetLab researchers are exploring several innovative solutions for searching and browsing in the subject-based Internet gateway, Electronic Engineering Library, Sweden (EELS). The implementation of the EELS service is described, specifically, the generation of the robot-gathered database 'All' engineering and the automated application of the Ei thesaurus and classification scheme. NetLab and OCLC researchers are collaborating to investigate advanced solutions to automated classification in the DESIRE II context. A plan for furthering the development of distributed vocabulary support in Internet search services is offered.
  2. Koch, T.; Ardö, A.; Noodén, L.: ¬The construction of a robot-generated subject index : DESIRE II D3.6a, Working Paper 1 (1999) 0.03
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    Abstract
    This working paper describes the creation of a test database to carry out the automatic classification tasks of the DESIRE II work package D3.6a on. It is an improved version of NetLab's existing "All" Engineering database created after a comparative study of the outcome of two different approaches to collecting the documents. These two methods were selected from seven different general methodologies to build robot-generated subject indices, presented in this paper. We found a surprisingly low overlap between the Engineering link collections we used as seed pages for the robot and subsequently an even more surprisingly low overlap between the resources collected by the two different approaches. That inspite of using basically the same services to start the harvesting process from. A intellectual evaluation of the contents of both databases showed almost exactly the same percentage of relevant documents (77%), indicating that the main difference between those aproaches was the coverage of the resulting database.
  3. Cheng, P.T.K.; Wu, A.K.W.: ACS: an automatic classification system (1995) 0.03
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    Abstract
    In this paper, we introduce ACS, an automatic classification system for school libraries. First, various approaches towards automatic classification, namely (i) rule-based, (ii) browse and search, and (iii) partial match, are critically reviewed. The central issues of scheme selection, text analysis and similarity measures are discussed. A novel approach towards detecting book-class similarity with Modified Overlap Coefficient (MOC) is also proposed. Finally, the design and implementation of ACS is presented. The test result of over 80% correctness in automatic classification and a cost reduction of 75% compared to manual classification suggest that ACS is highly adoptable
  4. Dubin, D.: Dimensions and discriminability (1998) 0.01
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    Date
    22. 9.1997 19:16:05
  5. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.01
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    Date
    1. 8.1996 22:08:06