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  • × theme_ss:"Automatisches Indexieren"
  1. Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016) 0.08
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    Date
    1. 2.2016 18:25:22
    Series
    Lecture notes in computer science ; 9398
  2. Newman, D.J.; Block, S.: Probabilistic topic decomposition of an eighteenth-century American newspaper (2006) 0.07
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    Abstract
    We use a probabilistic mixture decomposition method to determine topics in the Pennsylvania Gazette, a major colonial U.S. newspaper from 1728-1800. We assess the value of several topic decomposition techniques for historical research and compare the accuracy and efficacy of various methods. After determining the topics covered by the 80,000 articles and advertisements in the entire 18th century run of the Gazette, we calculate how the prevalence of those topics changed over time, and give historically relevant examples of our findings. This approach reveals important information about the content of this colonial newspaper, and suggests the value of such approaches to a more complete understanding of early American print culture and society.
    Date
    22. 7.2006 17:32:00
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.753-767
  3. Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983) 0.07
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    Abstract
    A study was done to test the effectiveness of retrieval using title word searching. It was based on actual search profiles used in the Mechanized Information Center at Ohio State University, in order ro replicate as closely as possible actual searching conditions. Fewer than 50% of the relevant titles were retrieved by keywords in titles. The low rate of retrieval can be attributes to three sources: titles themselves, user and information specialist ignorance of the subject vocabulary in use, and to general language problems. Across fields it was found that the social sciences had the best retrieval rate, with science having the next best, and arts and humanities the lowest. Ways to enhance and supplement keyword in title searching on the computer and in printed indexes are discussed.
    Date
    14. 3.1996 13:22:21
  4. Ward, M.L.: ¬The future of the human indexer (1996) 0.06
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    Abstract
    Considers the principles of indexing and the intellectual skills involved in order to determine what automatic indexing systems would be required in order to supplant or complement the human indexer. Good indexing requires: considerable prior knowledge of the literature; judgement as to what to index and what depth to index; reading skills; abstracting skills; and classification skills, Illustrates these features with a detailed description of abstracting and indexing processes involved in generating entries for the mechanical engineering database POWERLINK. Briefly assesses the possibility of replacing human indexers with specialist indexing software, with particular reference to the Object Analyzer from the InTEXT automatic indexing system and using the criteria described for human indexers. At present, it is unlikely that the automatic indexer will replace the human indexer, but when more primary texts are available in electronic form, it may be a useful productivity tool for dealing with large quantities of low grade texts (should they be wanted in the database)
    Date
    9. 2.1997 18:44:22
    Source
    Journal of librarianship and information science. 28(1996) no.4, S.217-225
  5. Milstead, J.L.: Thesauri in a full-text world (1998) 0.06
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    Abstract
    Despite early claims to the contemporary, thesauri continue to find use as access tools for information in the full-text environment. Their mode of use is changing, but this change actually represents an expansion rather than a contrdiction of their utility. Thesauri and similar vocabulary tools can complement full-text access by aiding users in focusing their searches, by supplementing the linguistic analysis of the text search engine, and even by serving as one of the tools used by the linguistic engine for its analysis. While human indexing contunues to be used for many databases, the trend is to increase the use of machine aids for this purpose. All machine-aided indexing (MAI) systems rely on thesauri as the basis for term selection. In the 21st century, the balance of effort between human and machine will change at both input and output, but thesauri will continue to play an important role for the foreseeable future
    Date
    22. 9.1997 19:16:05
    Imprint
    Urbana-Champaign, IL : Illinois University at Urbana-Champaign, Graduate School of Library and Information Science
    Source
    Visualizing subject access for 21st century information resources: Papers presented at the 1997 Clinic on Library Applications of Data Processing, 2-4 Mar 1997, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign. Ed.: P.A. Cochrane et al
  6. Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998) 0.05
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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
    Source
    Journal of the American Society for Information Science. 49(1998) no.10, S.888-902
  7. Croft, W.B.: Clustering large files of documents using the single link method (1977) 0.04
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    Source
    Journal of the American Society for Information Science. 28(1977), S.341-344
  8. 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) 0.04
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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
    Footnote
    Beitrag in einem Special Issue: Information Science in the German-speaking Countries.
    Source
    Aslib journal of information management. 71(2019) no.3, S.415-439
  9. Thiel, T.J.: Automated indexing of information stored on optical disk electronic document image management systems (1994) 0.04
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    Source
    Encyclopedia of library and information science. Vol.54, [=Suppl.17]
  10. Silvester, J.P.: Computer supported indexing : a history and evaluation of NASA's MAI system (1998) 0.04
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    Source
    Encyclopedia of library and information science. Vol.61, [=Suppl.24]
  11. Hlava, M.M.: Automatic indexing : a matter of degree (2002) 0.04
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    Source
    Bulletin of the American Society for Information Science. 28(2002) no.1, S.12-15
  12. Garfield, E.; Sher, I.H.: KeyWords Plus: algorithmic derivative indexing (1993) 0.04
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    Source
    Journal of the American Society for Information Science. 44(1993) no.5, S.298-299
  13. Dattola, R.T.: FIRST: Flexible information retrieval system for text (1979) 0.04
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    Source
    Journal of the American Society for Information Science. 30(1979), S.9-14
  14. Bookstein, A.; Swanson, D.R.: Probabilistic models for automatic indexing (1974) 0.04
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    Source
    Journal of the American Society for Information Science. 25(1974), S.312-318
  15. Garfield, E.; Sager, N.: Mechanical indexing, structural linguistics and information retrieval (1993) 0.04
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    Source
    Journal of information science. 19(1993) no.2, S.164-165
  16. Bordoni, L.; Pazienza, M.T.: Documents automatic indexing in an environmental domain (1997) 0.04
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    Abstract
    Describes an application of Natural Language Processing (NLP) techniques, in HIRMA (Hypertextual Information Retrieval Managed by ARIOSTO), to the problem of document indexing by referring to a system which incorporates natural language processing techniques to determine the subject of the text of documents and to associate them with relevant semantic indexes. Describes briefly the overall system, details of its implementation on a corpus of scientific abstracts related to environmental topics and experimental evidence of the system's behaviour. Analyzes in detail an experiment designed to evaluate the system's retrieval ability in terms of recall and precision
    Source
    International forum on information and documentation. 22(1997) no.1, S.17-28
  17. Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988) 0.03
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    Date
    16. 8.1998 12:51:22
    Source
    Proceedings of the 11th annual conference on research and development in information retrieval. Ed.: Y. Chiaramella
  18. Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998) 0.03
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    Source
    Information und Märkte: 50. Deutscher Dokumentartag 1998, Kongreß der Deutschen Gesellschaft für Dokumentation e.V. (DGD), Rheinische Friedrich-Wilhelms-Universität Bonn, 22.-24. September 1998. Hrsg. von Marlies Ockenfeld u. Gerhard J. Mantwill
  19. Tsareva, P.V.: Algoritmy dlya raspoznavaniya pozitivnykh i negativnykh vkhozdenii deskriptorov v tekst i protsedura avtomaticheskoi klassifikatsii tekstov (1999) 0.03
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    Date
    1. 4.2002 10:22:41
    Footnote
    Übers. des Titels: Algorithms for selection of positive and negative descriptors from text and automated text indexing
  20. Olsgaard, J.N.; Evans, E.J.: Improving keyword indexing (1981) 0.03
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    Abstract
    This communication examines some of the most frequently cited critisms of keyword indexing. These critisms include (1) absence of general subject headings, (2) limited entry points, and (3) irrelevant indexing. Some solutions are suggested to meet these critisms.
    Source
    Journal of the American society for information science. 32(1981), S.71-72

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