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Stochastic Modelling of Scientific Terms Distribution in Publications

  • Rimantas Rudzkis
  • Vaidas Balys
  • Michiel Hazewinkel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4108)

Abstract

In this paper, we address the problem of automatic keywords assignment to scientific publications. The idea to use textual traces learned from training data in a supervised manner to identify appropriate keywords is considered. We introduce the transparent concept of identification cloud as a means to represent the semantics of scientific terms. This concept is mathematically defined by models of scientific terms stochastic distributions over publication texts. Characteristics of models as well as procedures for both non-parametric and parametric estimation of probability distributions are presented.

Keywords

Support Vector Machine Latent Dirichlet Allocation Latent Semantic Analysis Scientific Term Probabilistic Latent Semantic Analysis 
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 2006

Authors and Affiliations

  • Rimantas Rudzkis
    • 1
  • Vaidas Balys
    • 1
  • Michiel Hazewinkel
    • 2
  1. 1.Institute of Mathematics and InformaticsVilniusLithuania
  2. 2.Centrum voor Wiskunde en InformaticaAmsterdamThe Netherlands

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