Search (98 results, page 1 of 5)

  • × theme_ss:"Automatisches Indexieren"
  1. Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988) 0.09
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    Date
    16. 8.1998 12:51:22
  2. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.09
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    Date
    14. 6.2015 22:12:56
    Source
    Automatische Indexierung zwischen Forschung und Anwendung, Hrsg.: G. Lustig
  3. Yongcheng, W.; Xiaoming, G.; Lixia, W.: Automatic indexing on subject of Chinese text (1998) 0.07
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    Abstract
    Outlines the underlying ideas, the basic algorithm and structure of CSAIS 2.1, an automatic indexing system for the subjects of Chinese documents, developed by the authors in 1993
  4. Blank, I.; Rokach, L.; Shani, G.: Leveraging metadata to recommend keywords for academic papers (2016) 0.04
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    Abstract
    Users of research databases, such as CiteSeerX, Google Scholar, and Microsoft Academic, often search for papers using a set of keywords. Unfortunately, many authors avoid listing sufficient keywords for their papers. As such, these applications may need to automatically associate good descriptive keywords with papers. When the full text of the paper is available this problem has been thoroughly studied. In many cases, however, due to copyright limitations, research databases do not have access to the full text. On the other hand, such databases typically maintain metadata, such as the title and abstract and the citation network of each paper. In this paper we study the problem of predicting which keywords are appropriate for a research paper, using different methods based on the citation network and available metadata. Our main goal is in providing search engines with the ability to extract keywords from the available metadata. However, our system can also be used for other applications, such as for recommending keywords for the authors of new papers. We create a data set of research papers, and their citation network, keywords, and other metadata, containing over 470K papers with and more than 2 million keywords. We compare our methods with predicting keywords using the title and abstract, in offline experiments and in a user study, concluding that the citation network provides much better predictions.
  5. Greiner-Petter, A.; Schubotz, M.; Cohl, H.S.; Gipp, B.: Semantic preserving bijective mappings for expressions involving special functions between computer algebra systems and document preparation systems (2019) 0.03
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    Abstract
    Purpose Modern mathematicians and scientists of math-related disciplines often use Document Preparation Systems (DPS) to write and Computer Algebra Systems (CAS) to calculate mathematical expressions. Usually, they translate the expressions manually between DPS and CAS. This process is time-consuming and error-prone. The purpose of this paper is to automate this translation. This paper uses Maple and Mathematica as the CAS, and LaTeX as the DPS. Design/methodology/approach Bruce Miller at the National Institute of Standards and Technology (NIST) developed a collection of special LaTeX macros that create links from mathematical symbols to their definitions in the NIST Digital Library of Mathematical Functions (DLMF). The authors are using these macros to perform rule-based translations between the formulae in the DLMF and CAS. Moreover, the authors develop software to ease the creation of new rules and to discover inconsistencies. Findings The authors created 396 mappings and translated 58.8 percent of DLMF formulae (2,405 expressions) successfully between Maple and DLMF. For a significant percentage, the special function definitions in Maple and the DLMF were different. An atomic symbol in one system maps to a composite expression in the other system. The translator was also successfully used for automatic verification of mathematical online compendia and CAS. The evaluation techniques discovered two errors in the DLMF and one defect in Maple. Originality/value This paper introduces the first translation tool for special functions between LaTeX and CAS. The approach improves error-prone manual translations and can be used to verify mathematical online compendia and CAS.
    Date
    20. 1.2015 18:30:22
  6. Dreis, G.: Formen des sachlichen Zugriffs : Probleme des automatischen Indexierens (1991) 0.03
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    Source
    Der Online-Publikumskatalog der Universitätsbibliothek Düsseldorf: methodische Erkenntnisse und Erfahrungen, OPAC-Kolloquium am 27. u.28.11.1989. Hrsg.: G. Gattermann
  7. Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998) 0.03
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    Abstract
    In this article, we describe and test a two-stage algorithm based on a lexical collocation technique which maps from the lexical clues contained in a document representation into a controlled vocabulary list of subject headings. Using a collection of 4.626 INSPEC documents, we create a 'dictionary' of associations between the lexical items contained in the titles, authors, and abstracts, and controlled vocabulary subject headings assigned to those records by human indexers using a likelihood ratio statistic as the measure of association. In the deployment stage, we use the dictiony to predict which of the controlled vocabulary subject headings best describe new documents when they are presented to the system. Our evaluation of this algorithm, in which we compare the automatically assigned subject headings to the subject headings assigned to the test documents by human catalogers, shows that we can obtain results comparable to, and consistent with, human cataloging. In effect we have cast this as a classic partial match information retrieval problem. We consider the problem to be one of 'retrieving' (or assigning) the most probably 'relevant' (or correct) controlled vocabulary subject headings to a document based on the clues contained in that document
    Date
    11. 9.2000 19:53:22
  8. Salton, G.; McGill, M. J.: Introduction to modern information retrieval (1983) 0.03
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  9. ¬The smart retrieval system : experiments in automatic document processing (1971) 0.03
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    Editor
    Salton, G.
  10. Research and development in information retrieval : Proc., Berlin, 18.-20.5.1982 (1983) 0.03
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    Editor
    Salton, G.; Schneider, H.-J.
  11. Salton, G.; Wong, A.: Generation and search of clustered files (1978) 0.03
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  12. Lustig, G.: Ist die automatische Indexierung bereits anwendbar? (1969) 0.03
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  13. Salton, G.; Yang, C.S.: On the specification of term values in automatic indexing (1973) 0.03
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  14. Yu, C.T.; Salton, G.: Precision weighting : an effective automatic indexing method (1976) 0.03
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  15. Knorz, G.: Automatisches Indexieren als Erkennen abstrakter Objekte (1983) 0.03
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  16. Biebricher, P.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬Das automatische Indexierungssystem AIR/PHYS (1988) 0.03
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  17. Peters, G.: Verschlagwortung und automatische Verfahren in der G+J Dokumentation (2003) 0.03
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  18. Salton, G.: ¬A new comparison between conventional indexing (MEDLARS) and automatic text processing (SMART) (1972) 0.03
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  19. Yu, C.T.; Salton, G.; Siu, M.K.: Effective automatic indexing using term addition and deletion (1978) 0.03
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  20. Gibb, F.; Smart, G.: Knowledge-based indexing : the view from SIMPR (1991) 0.03
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