Database tomography is an information extraction and analysis system which operates on textual databases. Its primary use to date has been to identify pervasive technical thrusts and themes, and the interrelationships among these themes and sub-themes which are intrinsic to large textual databases. Its two main algorithmic components are multi-word phrase frequency analysis and phrase proximity analysis. This paper shows how database tomography can be used to enhance information retrieval from large textual databases through the newly developed process of simulated nucleation. The principles of simulated nucleation are presented and the advantages for information retrieval are delineated. An application is described of developing a database of journal articles, focused on near-Earth space science and technology, from Science Citation Index and Engineering Compendex.


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    Titel :

    Database tomography for information retrieval


    Beteiligte:
    Kostoff, R.N. (Autor:in) / Eberhart, H.J. (Autor:in) / Toothman, D.R. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    1997


    Format / Umfang :

    11 Seiten, 32 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch






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