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Study of Knowledge Evolution in Parallel Computing by Short Texts Analysis

  • Pavel Makagonov
  • Alejandro Ruiz Figueroa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)

Abstract

The problem of measuring and predicting the future of various branches of science is discussed. We propose an economical approach that is useful for the estimation of the stage of development for any branch of “normal” science with the help of abstract flow analysis. For this goal it is necessary to collect large amounts of abstracts uniformly distributed in years. As abstracts are poor knowledge objects, we use the procedure of aggregation in its annual sum of texts as an elemental unit for cluster analysis. For cluster analysis we use the tool kit “Visual Heuristic Cluster Analysis for Texts” developed earlier by one of the co-authors, with K. Sboychakov. To determine the topic of the cluster, we propose to use chapters of manuals and articles principal in the procedure of pattern recognition.

Keywords

Virtual Machine Parallel Computing Message Passing Interface Poor Knowledge Knowledge Evolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Pavel Makagonov
    • 1
  • Alejandro Ruiz Figueroa
    • 2
  1. 1.Postgraduate Division of MixtecaUniversity of TechnologyHuajuapan de LeónMéxico
  2. 2.Institute of Electronic and Computation of Mixteca University of TechnologyHuajuapan de LeónMéxico

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